{
    "0.0.1": [{
        "5": {
            "title": "Using Python and microservices to fuel WebPush at Mozilla",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>In this talk, I\u2019ll be talking about how WebPush works, what are the key components involved and their roles in depth. Following this, I will be explaining how to build a webpush microservice written in Python for your application server.</p><p>Following is the break up of my talk:</p><p>What is Web Push?</p><ul><li>A brief about what the webpush technology is and how it works. </li><li>What are service workers and their role in webpush.</li><li>What are push servers and their role in webpush.</li><li>How to subscribe to push notifications</li></ul><p>How to build a webpush microservice using Python?</p><ul><li>What are the various components?</li><li>How to handle authentication for requests?</li><li>What are channels and how to implement them?</li><li>How to implement subscription to a channel?</li><li>How to implement publishing to a channel?</li></ul></p><p>In this talk, I\u2019ll be talking about how WebPush works, what are the key components involved and their roles in depth. Following this, I will be explaining how to build a webpush microservice written in Python for your application server.</p><p>Following is the break up of my talk:</p><p>What is Web Push?</p><p>How to build a webpush microservice using Python?</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><p>HTTP Verbs</p></p><p>HTTP Verbs</p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>https://docs.google.com/presentation/d/161Om8lLaXJYF5nqrYkoP8Zzm26Kxh8LpXAZ76LoYDSc/edit?usp=sharing</p></p><p>https://docs.google.com/presentation/d/161Om8lLaXJYF5nqrYkoP8Zzm26Kxh8LpXAZ76LoYDSc/edit?usp=sharing</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>Mansimar was a software developer intern at Mozilla and as part of her internship, developed a PubSub channels based push microservice. She has spoken at <a href=\"https://www.youtube.com/watch?v=Ld4PFVlbCPk&amp;t=9s\">FOSDEM 2017</a> and <a href=\"https://ep2017.europython.eu/en/\">EuroPython 2017</a> about the webpush technology and has written a series of <a href=\"https://medium.com/@mansimarkaur.mks\">articles</a>) about her work and webpush technology. She has worked on Brew as part of her Google Summer of Code with Homebrew. Previously, she worked on HackerRank's autocompletion service as an intern. Being an ardent open source enthusiast, she has contributed to Kinto - a minimalist JSON storage service, Brackets - a code editor by Adobe and also has a string of self-projects that she's proudly maintaining.</p></p><p>Mansimar was a software developer intern at Mozilla and as part of her internship, developed a PubSub channels based push microservice. She has spoken at <a href=\"https://www.youtube.com/watch?v=Ld4PFVlbCPk&amp;t=9s\">FOSDEM 2017</a> and <a href=\"https://ep2017.europython.eu/en/\">EuroPython 2017</a> about the webpush technology and has written a series of <a href=\"https://medium.com/@mansimarkaur.mks\">articles</a>) about her work and webpush technology. She has worked on Brew as part of her Google Summer of Code with Homebrew. Previously, she worked on HackerRank's autocompletion service as an intern. Being an ardent open source enthusiast, she has contributed to Kinto - a minimalist JSON storage service, Brackets - a code editor by Adobe and also has a string of self-projects that she's proudly maintaining.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p><a href=\"https://archive.fosdem.org/2017/schedule/event/python_kinto/\">FOSDEM 2017</a></p><p><a href=\"https://ep2017.europython.eu/conference/talks/using-python-and-microservices-to-fuel-webpush\">Europython 2017</a></p></p><p><a href=\"https://archive.fosdem.org/2017/schedule/event/python_kinto/\">FOSDEM 2017</a></p><p><a href=\"https://ep2017.europython.eu/conference/talks/using-python-and-microservices-to-fuel-webpush\">Europython 2017</a></p>",
            "date": "31 Aug, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/using-python-and-microservices-to-fuel-webpush-at-mozilla~b6KNd/",
            "speaker": {
                "name": "Mansimar Kaur (~mansimarkaur)",
                "info": "",
                "photo": ""
            }
        },
        "13": {
            "title": "PyBeacon: Eddystone Protocol implementation in Python",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>Eddystone is a protocol specification, an open beacon format from Google, that defines a Bluetooth low energy (BLE) message format for proximity beacon messages. It describes several different frame types that may be used individually or in combinations to create beacons that can be used for a variety of applications. PyBeacon is an Eddystone implementation in Python for Linux systems. Using this, Linux systems can be used as a beacon or a beacon scanner.</p></p><p>Eddystone is a protocol specification, an open beacon format from Google, that defines a Bluetooth low energy (BLE) message format for proximity beacon messages. It describes several different frame types that may be used individually or in combinations to create beacons that can be used for a variety of applications. PyBeacon is an Eddystone implementation in Python for Linux systems. Using this, Linux systems can be used as a beacon or a beacon scanner.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><ul><li>Should have a basic understanding of Python.</li></ul></p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><ul><li><a href=\"http://slides.com/prabhanshuattri/pybeacon-eddystone-protocol-implementation-in-python\">Drafted Presentation</a></li><li><a href=\"https://github.com/nirmankarta/PyBeacon\">PyBeacon</a></li><li><a href=\"https://github.com/google/eddystone/\">Eddystone</a></li><li><a href=\"https://pypi.python.org/pypi/PyBeacon\">PyBeacon on PyPi</a></li><li><a href=\"https://github.com/google/eddystone/tree/master/eddystone-url\">Eddystone URL Protocol</a></li><li><a href=\"https://github.com/google/eddystone/tree/master/eddystone-uid\">Eddystone UID Protocol</a></li><li><a href=\"https://github.com/google/eddystone/tree/master/eddystone-url/implementations/PyBeacon\">PyBeacon in Eddystone Repo</a></li></ul></p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>Prabhanshu Attri is a RGSoC Mentor, an open source enthusiast, IEEE CS Richard E Merwin Scholar and Former Summer Research Intern at Indian Institute of Technology Guwahati. He has also worked as a Software Development Engineer at Zomato.</p></p><p>Prabhanshu Attri is a RGSoC Mentor, an open source enthusiast, IEEE CS Richard E Merwin Scholar and Former Summer Research Intern at Indian Institute of Technology Guwahati. He has also worked as a Software Development Engineer at Zomato.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><ul><li><a href=\"http://prabhanshu.com\">Website</a></li><li><a href=\"http://prabhanshu.com/github-repo\">GitHub</a></li><li><a href=\"http://prabhanshu.com/linkedin\">LinkedIn</a></li></ul></p>",
            "date": "31 Aug, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/pybeacon-eddystone-protocol-implementation-in-python~eXpVe/",
            "speaker": {
                "name": "Prabhanshu Attri (~PrabhanshuAttri)",
                "info": "",
                "photo": ""
            }
        },
        "14": {
            "title": "Building microservices with firefly",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p><code>firefly</code> is an open source micro framework to deploy Python functions as web services. <code>firefly</code> was created with the aim of simplifying the deployment Machine Learning models as RESTful API. But as fate would have it, it became our favourite tool for building microservices. <code>firefly</code> takes care of processing the HTTP requests, forwarding the data to the python functions and encoding the result back to a HTTP request. It also has data validation, authentication support, transfering any type of file. You can also define a configuration file specifying the URL resource structure resulting in an elegant RESTful API.</p><p>It comes with a client library that makes calling remote functions calling as easy as calling functions present locally. It is a WSGI application and can be deployed and scaled through any WSGI server like <code>gunicorn</code>. There are many other features in the pipeline like multiple authentication modes through the plugin system.</p><p>This talk will focus on introducing <code>firefly</code>, it's notable features like plugin support, building microservices efficiently with various examples.</p></p><p><code>firefly</code> is an open source micro framework to deploy Python functions as web services. <code>firefly</code> was created with the aim of simplifying the deployment Machine Learning models as RESTful API. But as fate would have it, it became our favourite tool for building microservices. <code>firefly</code> takes care of processing the HTTP requests, forwarding the data to the python functions and encoding the result back to a HTTP request. It also has data validation, authentication support, transfering any type of file. You can also define a configuration file specifying the URL resource structure resulting in an elegant RESTful API.</p><p>It comes with a client library that makes calling remote functions calling as easy as calling functions present locally. It is a WSGI application and can be deployed and scaled through any WSGI server like <code>gunicorn</code>. There are many other features in the pipeline like multiple authentication modes through the plugin system.</p><p>This talk will focus on introducing <code>firefly</code>, it's notable features like plugin support, building microservices efficiently with various examples.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><p>The participants should have a basic notion of making web services and RESTful API's.</p></p><p>The participants should have a basic notion of making web services and RESTful API's.</p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>Slides outline:</p><ol><li>About me</li><li>Microservices Architecture</li><li>Comparison with monolithic architecture</li><li>Design Patterns</li><li>Forces in Action</li><li>Solution</li><li>Examples</li><li>Benfits</li><li>When to use?</li><li>Who uses?</li><li>Firefly to the rescue</li><li>What is firefly?</li><li>Why use firefly?</li><li>Code</li><li>Run</li><li>Deploy</li><li>Use (Client)</li><li>Authentication</li><li>Data Validation</li><li>Canonical URL's</li><li>Plugins</li></ol><p>Github: <a href=\"https://github.com/rorodata/firefly\">https://github.com/rorodata/firefly</a><br/>Documentation: <a href=\"https://firefly-python.readthedocs.io/\">https://firefly-python.readthedocs.io/</a></p></p><p>Slides outline:</p><p>Github: <a href=\"https://github.com/rorodata/firefly\">https://github.com/rorodata/firefly</a><br/>Documentation: <a href=\"https://firefly-python.readthedocs.io/\">https://firefly-python.readthedocs.io/</a></p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>The speaker is Nabarun Pal, a final year undergraduate student at <a href=\"http://iitr.ac.in\">Indian Institute of Technology Roorkee</a>. Currently, he is working for <a href=\"https://rorodata.com\">rorodata</a> which aims at providing data scientists a platform to build and deploy their models without the need of worrying about infrastructure, scalability, and performance. He is working on an Open Source Functions as a Service framework called <a href=\"https://github.com/rorodata/firefly\">firefly</a>.</p><p>He is passionate about software development. He can also talk about Internet of Things, Electronics, Robotics with equal spirit. His journey with the field of software and robotics started in his schooling days. He represents the college in various Robotics competitions and was involved in projects related to the above domains, brief of which can be found <a href=\"https://nabarun.in/Nabarun_Pal_SDE.pdf\">here</a>. He actively participates in conducting open lectures for students in the domains of Introductory Robotics, Control, AI and ML through a curated <a href=\"https://www.facebook.com/groups/mnrsectioniitr/\">community</a> of around 2000 members. He is also speaking at <a href=\"http://www.pydata.org/delhi2017\">PyData Delhi 2017</a>.</p></p><p>The speaker is Nabarun Pal, a final year undergraduate student at <a href=\"http://iitr.ac.in\">Indian Institute of Technology Roorkee</a>. Currently, he is working for <a href=\"https://rorodata.com\">rorodata</a> which aims at providing data scientists a platform to build and deploy their models without the need of worrying about infrastructure, scalability, and performance. He is working on an Open Source Functions as a Service framework called <a href=\"https://github.com/rorodata/firefly\">firefly</a>.</p><p>He is passionate about software development. He can also talk about Internet of Things, Electronics, Robotics with equal spirit. His journey with the field of software and robotics started in his schooling days. He represents the college in various Robotics competitions and was involved in projects related to the above domains, brief of which can be found <a href=\"https://nabarun.in/Nabarun_Pal_SDE.pdf\">here</a>. He actively participates in conducting open lectures for students in the domains of Introductory Robotics, Control, AI and ML through a curated <a href=\"https://www.facebook.com/groups/mnrsectioniitr/\">community</a> of around 2000 members. He is also speaking at <a href=\"http://www.pydata.org/delhi2017\">PyData Delhi 2017</a>.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p>Homepage: <a href=\"https://nabarun.in\">https://nabarun.in</a><br/>LinkedIn: <a href=\"https://www.linkedin.com/in/nabarunpal/\">https://www.linkedin.com/in/nabarunpal/</a><br/>Github: <a href=\"https://github.com/palnabarun\">https://github.com/palnabarun</a></p></p><p>Homepage: <a href=\"https://nabarun.in\">https://nabarun.in</a><br/>LinkedIn: <a href=\"https://www.linkedin.com/in/nabarunpal/\">https://www.linkedin.com/in/nabarunpal/</a><br/>Github: <a href=\"https://github.com/palnabarun\">https://github.com/palnabarun</a></p>",
            "date": "31 Aug, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/building-microservices-with-firefly~bWoob/",
            "speaker": {
                "name": "Nabarun Pal (~palnabarun)",
                "info": "",
                "photo": ""
            }
        },
        "16": {
            "title": "Liberating tabular data from the clutches of PDFs",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>Budget Documents are moral documents that represent the priorities and values of the states and its governing bodies. Unfortunately these documents are published in unstructured PDF formats which makes it difficult for researchers, economists and general public to analyse and use this crucial data. </p><p>In this session will delve into how we can create a data pipeline and leverage computer vision techniques to parse these documents into clean machine-readable formats by leveraging libraries like OpenCV, numpy, pandas, PyPDF2, tabula and poppler-pdf-to-text</p><p><strong>Outline</strong></p><ul><li>Setting the scene</li><li>Issues with Indian Budget Documents</li><li>Extracting Tables with boundaries.<ul><li>Detecting Table Boundaries using OpenCV</li><li>Leveraging Open Source Tools like \u201cTabula\u201d</li></ul></li><li>What about tables without boundaries ?</li><li>Extracting information from tables without boundaries<ul><li>Geometrical features using OpenCV library</li><li>Textual features using \u201cpdf to text\u201d poppler\u2019s version</li></ul></li><li>Building a pipeline to detect table components<ul><li>Headers</li><li>Number Cells</li><li>Text Based Cells / Groupings</li></ul></li><li>Detecting Table layout<ul><li>Detecting rows</li><li>Detecting columns</li><li>Where each component lies</li></ul></li><li>Extracting tables split across Pages</li><li>Building a base for machine learning models while doing so.</li><li>Open Research using Jupyter Notebooks</li><li>How you can contribute ?</li></ul></p><p>Budget Documents are moral documents that represent the priorities and values of the states and its governing bodies. Unfortunately these documents are published in unstructured PDF formats which makes it difficult for researchers, economists and general public to analyse and use this crucial data. </p><p>In this session will delve into how we can create a data pipeline and leverage computer vision techniques to parse these documents into clean machine-readable formats by leveraging libraries like OpenCV, numpy, pandas, PyPDF2, tabula and poppler-pdf-to-text</p><p><strong>Outline</strong></p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><ul><li>Python 2.7</li><li>pandas</li><li>numpy</li><li>Basic Image Manipulation using OpenCV</li></ul></p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>Repo: https://github.com/heaven00/pycon_delhi_2017 <br/>Slides: https://heaven00.github.io/pycon_delhi_2017</p></p><p>Repo: https://github.com/heaven00/pycon_delhi_2017 <br/>Slides: https://heaven00.github.io/pycon_delhi_2017</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>Jayant works with Open Budgets India to help make India's Budgets open, usable and easy to comprehend and during the weekends he works with Datakind as a core team member to help make social organisations data driven.</p><p>Jayant is also a machine learning enthusiast and enjoys good food and games.</p></p><p>Jayant works with Open Budgets India to help make India's Budgets open, usable and easy to comprehend and during the weekends he works with Datakind as a core team member to help make social organisations data driven.</p><p>Jayant is also a machine learning enthusiast and enjoys good food and games.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><ul><li>https://github.com/cbgaindia/parsers</li><li>https://github.com/cbgaindia/scrapers </li><li>https://github.com/heaven00</li></ul></p>",
            "date": "31 Aug, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/liberating-tabular-data-from-the-clutches-of-pdfs~dRjwd/",
            "speaker": {
                "name": "jayant (~heaven00)",
                "info": "",
                "photo": ""
            }
        },
        "24": {
            "title": "HTTP Bottom Up - Live!",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>A deep-dive, live coding talk to explore everything that happens behind the scenes of your favorite web framework.</p><p>This talk explores building web applications starting all the way from bare sockets, without using any framework. Even though this is not the most production way to build web applications, this exercise will give a chance to observe and understand everything that happens behind the scenes of any web application.</p><h3>Outline</h3><ul><li>Understand the difference between the Internet and World Wide Web</li><li>Play with some Internet Applications</li><li>Network programming and concurrency patterns</li><li>Understand how web browser and web server work</li><li>Build a web server</li><li>Understand WSGI</li><li>Build a web framework</li><li>Write a simple webapp using the web framework built above</li></ul></p><p>A deep-dive, live coding talk to explore everything that happens behind the scenes of your favorite web framework.</p><p>This talk explores building web applications starting all the way from bare sockets, without using any framework. Even though this is not the most production way to build web applications, this exercise will give a chance to observe and understand everything that happens behind the scenes of any web application.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><p>Open mind and curiosity.</p></p><p>Open mind and curiosity.</p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>This is going to be a live coding talk. I'm not planning to use any slides.</p><p>I offer this as a 2-day workshop and notes from one my earlier workshops are available at:  <br/><a href=\"https://github.com/anandology/httpbottomup\">https://github.com/anandology/httpbottomup</a></p></p><p>This is going to be a live coding talk. I'm not planning to use any slides.</p><p>I offer this as a 2-day workshop and notes from one my earlier workshops are available at:  <br/><a href=\"https://github.com/anandology/httpbottomup\">https://github.com/anandology/httpbottomup</a></p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p><a href=\"http://anandology.com/\">Anand</a> has been crafting beautiful software since a decade and half. He\u2019s now building a data science platform, <a href=\"http://rorodata.com/\">rorodata</a>, which he recently co-founded. He regularly conducts advanced programming courses through <a href=\"https://pipal.in/\">Pipal Academy</a>. He is co-author of web.py, a micro web framework in Python. He has worked at Strand Life Sciences and Internet Archive.</p></p><p><a href=\"http://anandology.com/\">Anand</a> has been crafting beautiful software since a decade and half. He\u2019s now building a data science platform, <a href=\"http://rorodata.com/\">rorodata</a>, which he recently co-founded. He regularly conducts advanced programming courses through <a href=\"https://pipal.in/\">Pipal Academy</a>. He is co-author of web.py, a micro web framework in Python. He has worked at Strand Life Sciences and Internet Archive.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p><a href=\"http://anandology.com/\">http://anandology.com/</a></p></p><p><a href=\"http://anandology.com/\">http://anandology.com/</a></p>",
            "date": "31 Aug, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/http-bottom-up-live~bDWka/",
            "speaker": {
                "name": "Anand Chitipothu (~anandology)",
                "info": "",
                "photo": ""
            }
        },
        "51": {
            "title": "Reducing dead code ratio of your project with vulture",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>Maintaining a high level of code quality is important for any serious project. One aspect of this is ensuring that all code is actually used. There are many reasons for dead code ending up in a project. The most common is refactoring, but another is misspellings, which are only detected at runtime for dynamic languages. Finding and removing dead code allows to keep the code base clean and reduces bugs. </p><p>This talk is focussed on how we can use Vulture to find dead code. It helps you find unused code in Python programs and it is useful for cleaning up and finding errors in large code bases. If you run Vulture on both your library and test suite you can find untested code. Due to Python's dynamic nature, static code analyzers like Vulture are likely to miss some dead code. Also, code that is only called implicitly may be reported as unused. Nonetheless, Vulture can be a very helpful tool for higher code quality.</p><p>One part of this talk is to discuss how to automate testing for dead code with Vulture. There are quite a few options available:</p><ul><li>Adding vulture to your continuous integration testing.</li><li>A script using the Vulture API for custom tests.</li><li><a href=\"https://github.com/coala/coala-bears/blob/master/bears/python/VultureBear.py\">VultureBear</a>: Integration with <a href=\"https://coala.io\">coala</a> - a static code analysis tool.</li><li>Integration with automatic analysis tools like <a href=\"https://gitmate.io\">GitMate</a>, etc. for automatic code-reviews with native support for Github and Gitlab.</li></ul></p><p>Maintaining a high level of code quality is important for any serious project. One aspect of this is ensuring that all code is actually used. There are many reasons for dead code ending up in a project. The most common is refactoring, but another is misspellings, which are only detected at runtime for dynamic languages. Finding and removing dead code allows to keep the code base clean and reduces bugs. </p><p>This talk is focussed on how we can use Vulture to find dead code. It helps you find unused code in Python programs and it is useful for cleaning up and finding errors in large code bases. If you run Vulture on both your library and test suite you can find untested code. Due to Python's dynamic nature, static code analyzers like Vulture are likely to miss some dead code. Also, code that is only called implicitly may be reported as unused. Nonetheless, Vulture can be a very helpful tool for higher code quality.</p><p>One part of this talk is to discuss how to automate testing for dead code with Vulture. There are quite a few options available:</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><ul><li>python (any version would do)</li><li>pip</li></ul><p>Having coala installed will be a plus.</p></p><p>Having coala installed will be a plus.</p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><ul><li><p><a href=\"https://github.com/jendrikseipp/vulture\">vulture</a></p></li><li><p><a href=\"https://coala.io\">coala.io</a></p></li><li><p><a href=\"https://gitmate.io\">GitMate</a></p></li></ul></p><p><a href=\"https://github.com/jendrikseipp/vulture\">vulture</a></p><p><a href=\"https://coala.io\">coala.io</a></p><p><a href=\"https://gitmate.io\">GitMate</a></p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p><strong>Rahul Jha</strong></p><p>He is currently pursuing B.Tech. (ECE) and has been developing software for 3 years now. He is an Open source enthusiast and as part of his GSoC project, he developed the vulture API for easy integration with coala.</p></p><p><strong>Rahul Jha</strong></p><p>He is currently pursuing B.Tech. (ECE) and has been developing software for 3 years now. He is an Open source enthusiast and as part of his GSoC project, he developed the vulture API for easy integration with coala.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p>You may find more about Rahul here:</p><ul><li><a href=\"https://github.com/RJ722\">https://github.com/RJ722</a></li><li><a href=\"https://rj722.tech\">https://rj722.tech</a></li></ul><p>The best way to contact him is through e-mail: rahul722j@gmail.com, rahul@rj722.tech</p><p>Some of his work:</p><ul><li><a href=\"https://github.com/jendrikseipp/vulture/commits?author=RJ722\">https://github.com/jendrikseipp/vulture/commits?author=RJ722</a></li><li><a href=\"https://github.com/coala/coala-bears/commits?author=RJ722\">https://github.com/coala/coala-bears/commits?author=RJ722</a></li><li><a href=\"https://github.com/coala/coala/commits?author=RJ722\">https://github.com/coala/coala/commits?author=RJ722</a></li></ul></p><p>You may find more about Rahul here:</p><p>The best way to contact him is through e-mail: rahul722j@gmail.com, rahul@rj722.tech</p><p>Some of his work:</p>",
            "date": "28 Aug, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/reducing-dead-code-ratio-of-your-project-with-vulture~e9GYb/",
            "speaker": {
                "name": "Rahul Jha (~RJ722)",
                "info": "",
                "photo": ""
            }
        },
        "57": {
            "title": "A little bot for empowering teams",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>The talk is about a bot which has potential to solve/prevent communication problems at workplace.  Don't buy it yet? read on:</p><p><strong>Outline of Talk:</strong></p><ul><li>Problem analysis &amp; origin of the bot - 10 min</li><li>The bot at your service - 15 min<ul><li>with a live demo, we will discover, how we got our first bot live and then what more handy features it brought @ work that it is like a team member now and how does it solves the problems.</li></ul></li><li>The exponential future possibilities - 5 min</li><li>Questions &amp; Answers - 5 min</li></ul><p><strong>What is in it for me:</strong></p><p>Imagine, it is one of your Release Day and the code started breaking all of a sudden, tested features are not working anymore, and it is going to take time to figure out whom to reach &amp; people start passing the buck?</p><p><img alt=\"enter image description here\" src=\"https://s3.amazonaws.com/qa-ops/no.gif\"/>              Experienced such stormy sail on your release day?</p><p>Amidst all this, <strong>losing time for release</strong> deployment as the traffic on your product is peaking up or exceeding the deadline promised to the clients. Manual monitoring wasn\u2019t a solution as it isn\u2019t scalable ?</p><ul><li>Already nodding your head in agreement ? Many times somewhere deep down, did you feel like escaping from the heated discussion or wished there were snapshots of all the important events which could give you the clues/traceback to hunt &amp; chuck the wrong commits out of the system and move ahead. Or even better some software which you could just hook to your system which would never let you reach such a chaotic state itself by blocking/notifying any wrong doings.</li><li>Or are you among those telling yourself \u201cwe already solved it\u201d. As a tech geek, are you excited to explore a different way as to how we are solving it?</li></ul><p>Come let\u2019s talk and take a sneak peek at how we are dealing with these and how Project <a href=\"https://github.com/moengage/alice\">Alice</a> is helping us.</p><ul><li>Will also be sharing how I leveraged the power of existing <strong>Open Sourced technologies</strong> along with beauty of <strong>python</strong> to create it.</li><li>How this can be useful for many of your use cases at work and know how you can also create your own personal 24*7 guard/assistant for your team.</li></ul><p>~ A little attempt towards making healthier work culture by keeping the smart brains happier :-)</p></p><p>The talk is about a bot which has potential to solve/prevent communication problems at workplace.  Don't buy it yet? read on:</p><p><strong>Outline of Talk:</strong></p><p><strong>What is in it for me:</strong></p><p>Imagine, it is one of your Release Day and the code started breaking all of a sudden, tested features are not working anymore, and it is going to take time to figure out whom to reach &amp; people start passing the buck?</p><p><img alt=\"enter image description here\" src=\"https://s3.amazonaws.com/qa-ops/no.gif\"/>              Experienced such stormy sail on your release day?</p><p>Amidst all this, <strong>losing time for release</strong> deployment as the traffic on your product is peaking up or exceeding the deadline promised to the clients. Manual monitoring wasn\u2019t a solution as it isn\u2019t scalable ?</p><p>Come let\u2019s talk and take a sneak peek at how we are dealing with these and how Project <a href=\"https://github.com/moengage/alice\">Alice</a> is helping us.</p><p>~ A little attempt towards making healthier work culture by keeping the smart brains happier :-)</p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>Open sourced - <a href=\"https://github.com/moengage/alice\">Alice</a> the bot</p><p>PPT link - will attach soon</p></p><p>Open sourced - <a href=\"https://github.com/moengage/alice\">Alice</a> the bot</p><p>PPT link - will attach soon</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>Pooja is an automation nerd and open source enthusiast. She loves brainstorming and implementing crazy ideas to figure out ways to improve the product quality. Having a blend of dev, qa &amp; devops mindset, she strives to bridge the gaps between all the teams to attain the best results. Driven by curiosity to learn &amp; share new things everyday, she blogs, speaks &amp; records 'easy to learn' tutorials.</p></p><p>Pooja is an automation nerd and open source enthusiast. She loves brainstorming and implementing crazy ideas to figure out ways to improve the product quality. Having a blend of dev, qa &amp; devops mindset, she strives to bridge the gaps between all the teams to attain the best results. Driven by curiosity to learn &amp; share new things everyday, she blogs, speaks &amp; records 'easy to learn' tutorials.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><ul><li><a href=\"https://p00j4.github.io/#four\">Open Source Contributions</a></li><li><a href=\"https://www.youtube.com/channel/UCuTeHYWpoP5OWP5UtkdEV-Q/playlists\">Previous Talks</a></li><li><a href=\"https://twitter.com/TechGirlPooja\">Twitter</a></li></ul></p>",
            "date": "25 Aug, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/a-little-bot-for-empowering-teams~e1EGe/",
            "speaker": {
                "name": "Pooja Shah (~p00j4)",
                "info": "",
                "photo": ""
            }
        },
        "60": {
            "title": "Applying Transfer Learning on Your Data",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>Humans have great ability to generalize; we can very efficiently apply the knowledge we learned in classrooms to real world problems. <strong>Transfer learning</strong> provides a similar capability to artificial neural networks. The Workshop will introduce the concept of 'Transfer Learning' described by Andrew Ng, the leading expert in Machine Learning as the \"<strong>next driver of ML commercial success.</strong>\" Transfer Learning is important because training deep neural networks from scratch have two key requirements. First, we need a large labeled dataset; the second one requires computationally efficient hardware (GPUs). While such immensely large data exists for some tasks and domains, in most cases the data are usually proprietary or expensive. Transfer Learning, the technique to use models pre-trained on one domain for another problem domain, provides the ability to use DNNs even when the dataset is small. Moreover, Transfer learning requires less computation and thus can be done in respectable time using CPUs as well.</p><p>The workshop will cover following topics:</p><ul><li>Introduction to Transfer Learning </li><li>Application of Transfer Learning</li><li>Transfer Learning Scenarios </li><li>Applying Transfer using Keras and Tensorflow</li></ul><p>And finally, we will have hands on session demonstrating how to use Xception and Inception networks for Dog breed Recognition.</p></p><p>Humans have great ability to generalize; we can very efficiently apply the knowledge we learned in classrooms to real world problems. <strong>Transfer learning</strong> provides a similar capability to artificial neural networks. The Workshop will introduce the concept of 'Transfer Learning' described by Andrew Ng, the leading expert in Machine Learning as the \"<strong>next driver of ML commercial success.</strong>\" Transfer Learning is important because training deep neural networks from scratch have two key requirements. First, we need a large labeled dataset; the second one requires computationally efficient hardware (GPUs). While such immensely large data exists for some tasks and domains, in most cases the data are usually proprietary or expensive. Transfer Learning, the technique to use models pre-trained on one domain for another problem domain, provides the ability to use DNNs even when the dataset is small. Moreover, Transfer learning requires less computation and thus can be done in respectable time using CPUs as well.</p><p>The workshop will cover following topics:</p><p>And finally, we will have hands on session demonstrating how to use Xception and Inception networks for Dog breed Recognition.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><ul><li>Anaconda installed (Python =3.5)</li><li>Tensorflow 1.x</li><li>Numpy</li><li>Matplotlib</li><li>Pandas</li><li>Seaborn</li><li>For the sake of convenience and due to limited time, Speaker, will also provide environment 'yml' files (Windows10, Ubuntu14.04/16.04, Mac OS X)</li></ul></p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>To make best use of the workshop it would be appreciated if participants are well versed with Anaconda, Python and understand Convolution Neural Networks. The information necessary can be accessed via following links</p><ul><li>How to manage Anaconda Environments:  <a href=\"https://conda.io/docs/user-guide/tasks/manage-environments.html\">https://conda.io/docs/user-guide/tasks/manage-environments.html</a> </li><li>Convolutional Neural Networks <a href=\"https://adeshpande3.github.io/adeshpande3.github.io/A-Beginner%27s-Guide-To-Understanding-Convolutional-Neural-Networks/\">here</a> and <a href=\"http://colah.github.io/posts/2014-07-Conv-Nets-Modular/\">here</a></li></ul></p><p>To make best use of the workshop it would be appreciated if participants are well versed with Anaconda, Python and understand Convolution Neural Networks. The information necessary can be accessed via following links</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p><strong>Amita Kapoor</strong>: Amita Kapoor is Associate Professor in the Department of Electronics, SRCASW, University of Delhi. She has been actively teaching neural networks for last twenty years. She did her Masters in Electronics in the year 1996, and her PhD in the year 2011. During the course of her PhD, she was awarded prestigious DAAD fellowship to pursue a part of her research work in Karlsruhe Institute of Technology, Karlsruhe, Germany. She had been awarded best Presentation Award at International Conference Photonics 2008 for her paper. She is a member of professional bodies like OSA (Optical Society of America), IEEE (Institute of Electrical and Electronics Engineers), INNS (International Neural Network Society), ISBS (Indian Society for Buddhist Studies). She has more than 40 publications in the international journals and conferences. Her present research areas include Machine Learning, Artificial Intelligence, Neural Networks, Photonics and Robotics.</p><p><strong>Narotam Singh</strong>: Narotam Singh has been with India Meteorological Department, Ministry of Earth Sciences, India since 1996.  He has been actively involved with various technical programs and training of officers of GOI in the field of Information Technology and Communication. He did his post-graduation in the field of Electronics in 1996 and both Post graduate diploma and Diploma in the field of Computer Engineering, in 1997 and 1994 respectively. He is currently working in the enigmatic field of Neural Networks.</p></p><p><strong>Amita Kapoor</strong>: Amita Kapoor is Associate Professor in the Department of Electronics, SRCASW, University of Delhi. She has been actively teaching neural networks for last twenty years. She did her Masters in Electronics in the year 1996, and her PhD in the year 2011. During the course of her PhD, she was awarded prestigious DAAD fellowship to pursue a part of her research work in Karlsruhe Institute of Technology, Karlsruhe, Germany. She had been awarded best Presentation Award at International Conference Photonics 2008 for her paper. She is a member of professional bodies like OSA (Optical Society of America), IEEE (Institute of Electrical and Electronics Engineers), INNS (International Neural Network Society), ISBS (Indian Society for Buddhist Studies). She has more than 40 publications in the international journals and conferences. Her present research areas include Machine Learning, Artificial Intelligence, Neural Networks, Photonics and Robotics.</p><p><strong>Narotam Singh</strong>: Narotam Singh has been with India Meteorological Department, Ministry of Earth Sciences, India since 1996.  He has been actively involved with various technical programs and training of officers of GOI in the field of Information Technology and Communication. He did his post-graduation in the field of Electronics in 1996 and both Post graduate diploma and Diploma in the field of Computer Engineering, in 1997 and 1994 respectively. He is currently working in the enigmatic field of Neural Networks.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p>Amita Kapoor: <a href=\"http://www.dramitakapoor.com\">Personal Website</a>, <a href=\"https://github.com/amita-kapoor\">Github</a>, <a href=\"https://www.linkedin.com/in/amitakapoor/\">Linkedin</a></p><p>Narotam Singh: <a href=\"http://narotam.com/\">Personal Website</a>, <a href=\"https://github.com/narotamsingh\">Github</a>, <a href=\"https://www.linkedin.com/in/narotamsingh/\">Linkedin</a></p></p><p>Amita Kapoor: <a href=\"http://www.dramitakapoor.com\">Personal Website</a>, <a href=\"https://github.com/amita-kapoor\">Github</a>, <a href=\"https://www.linkedin.com/in/amitakapoor/\">Linkedin</a></p><p>Narotam Singh: <a href=\"http://narotam.com/\">Personal Website</a>, <a href=\"https://github.com/narotamsingh\">Github</a>, <a href=\"https://www.linkedin.com/in/narotamsingh/\">Linkedin</a></p>",
            "date": "25 Aug, 2017",
            "type": "workshop",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/applying-transfer-learning-on-your-data~eXqoa/",
            "speaker": {
                "name": "Amita Kapoor (~amita)",
                "info": "",
                "photo": ""
            }
        },
        "65": {
            "title": "Python packages",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>All of our scripts need to eventually grow up into packages. Over the course of this workshop, I'll help grow your script/scripts into fully fledged packages.</p><p>We will start with a basic <code>setup.py</code> file and understand how installing a package makes it easy to use. We will look at examples of how to organise our package and understand how the organisation helps in understanding the package. We will use entry points to make your package more accessible. We will learn how GitHub can be used to host and share your package and what role Git plays. We will understand the role of Continuous Integration services. Finally, we will build and upload eggs &amp; wheels for your package to PyPI.</p></p><p>All of our scripts need to eventually grow up into packages. Over the course of this workshop, I'll help grow your script/scripts into fully fledged packages.</p><p>We will start with a basic <code>setup.py</code> file and understand how installing a package makes it easy to use. We will look at examples of how to organise our package and understand how the organisation helps in understanding the package. We will use entry points to make your package more accessible. We will learn how GitHub can be used to host and share your package and what role Git plays. We will understand the role of Continuous Integration services. Finally, we will build and upload eggs &amp; wheels for your package to PyPI.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><p>It would help if the participants had a basic understanding of Python syntax.It will also help if the participants knew how to use Git and how to navigate GitHub.Neither is a concrete requirement though.</p></p><p>It would help if the participants had a basic understanding of Python syntax.It will also help if the participants knew how to use Git and how to navigate GitHub.Neither is a concrete requirement though.</p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>The workshop will extend and elaborate on slides from an earlier talk - https://github.com/rahulporuri/talks/blob/master/python_packages.pdf</p><p>Git and GitHub will also be introduced and used for the workshop; slides from an earlier workshop are - https://github.com/rahulporuri/talks/blob/master/git_and_github.pdf</p></p><p>The workshop will extend and elaborate on slides from an earlier talk - https://github.com/rahulporuri/talks/blob/master/python_packages.pdf</p><p>Git and GitHub will also be introduced and used for the workshop; slides from an earlier workshop are - https://github.com/rahulporuri/talks/blob/master/git_and_github.pdf</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>I am a Scientific Software Developer at Enthought. By day, I work on Enthought's Product offerings. I have a background in Physics. I like giving talks and conducting workshops because researching the topic increases my understanding. I've been (semi-) active in the Python community in Pune over the last year and I've given talks at local meetups and organized workshops.</p></p><p>I am a Scientific Software Developer at Enthought. By day, I work on Enthought's Product offerings. I have a background in Physics. I like giving talks and conducting workshops because researching the topic increases my understanding. I've been (semi-) active in the Python community in Pune over the last year and I've given talks at local meetups and organized workshops.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p>Links to slides and Jupyter Notebooks for some of the talks/workshops I conducted over the last year - https://github.com/rahulporuri/talks/</p></p><p>Links to slides and Jupyter Notebooks for some of the talks/workshops I conducted over the last year - https://github.com/rahulporuri/talks/</p>",
            "date": "24 Aug, 2017",
            "type": "workshop",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/python-packages~dPr2a/",
            "speaker": {
                "name": "rahul .poruri (~rahul66)",
                "info": "",
                "photo": ""
            }
        },
        "90": {
            "title": "Pyspark - Big Data applications using Python and Spark",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>Here is the high level outline for the workshop:</p><ul><li>Revision of basic python programming</li><li>Overview of Big Data eco system</li><li>Data Engineering at scale with Spark core APIs using Python as programming language</li><li>Overvew of Spark SQL and Data Frames</li><li>Development life cycle and execution life cycle</li></ul><p>Training will be provided using state of the art 10 node Big Data cluster. If this workshop is selected, all the participants for the workshop will get 1 month free access to our state of the art lab with content and other resources to learn Big Data in detail.</p><p>If you are interested in this workshop please vote up to get shortlisted.</p></p><p>Here is the high level outline for the workshop:</p><p>Training will be provided using state of the art 10 node Big Data cluster. If this workshop is selected, all the participants for the workshop will get 1 month free access to our state of the art lab with content and other resources to learn Big Data in detail.</p><p>If you are interested in this workshop please vote up to get shortlisted.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><ul><li>A laptop (64 bit operating system and 4 GB RAM are highly desired)</li><li>Browser - Chrome or Firefox</li><li>Basic understanding of Python programming - loops, exception, file handling and collections</li></ul></p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>http://www.itversity.com/courses/apache-spark-using-python</p></p><p>http://www.itversity.com/courses/apache-spark-using-python</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>Durga Gadiraju is technology evangelist and consultant with close to 14 years of experience in building data driven applications at scale. For past 4 years, Durga is primarily focused on Big Data in the areas of consulting, delivery and training. His online platform itversity, is well known in IT community in the areas of Big Data and Cloud. itversity will be a free continuous learning platform for IT professionals.</p></p><p>Durga Gadiraju is technology evangelist and consultant with close to 14 years of experience in building data driven applications at scale. For past 4 years, Durga is primarily focused on Big Data in the areas of consulting, delivery and training. His online platform itversity, is well known in IT community in the areas of Big Data and Cloud. itversity will be a free continuous learning platform for IT professionals.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><ul><li>LinkedIN <a href=\"http://%20https://www.linkedin.com/in/durga0gadiraju/\">Profile</a></li><li>YouTube <a href=\"https://www.YouTube.com/itversityin\">Channel</a></li><li><a href=\"http://www.itversity.com\">Blog</a></li><li>Big Data <a href=\"https://labs.itversity.com\">labs</a></li><li>Support through <a href=\"http://discuss.itversity.com\">Forums</a></li><li>Github <a href=\"https://github.com/dgadiraju\">account</a></li></ul></p>",
            "date": "09 Aug, 2017",
            "type": "workshop",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/pyspark-big-data-applications-using-python-and-spark~b44kb/",
            "speaker": {
                "name": "Itversity Training (~itversity)",
                "info": "",
                "photo": ""
            }
        },
        "94": {
            "title": "Geospatial data science and analysis using ArcGIS API for Python",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>Analysts and data scientists can use the ArcGIS API in combination with data science libraries in Python for mapping, visualization and geospatial data analysis.  This live-demo style talk will demonstrate how to perform sophisticated vector and raster analysis, geocoding, map making, routing and directions using a Pythonic API along with Jupyter notebooks and Pandas.</p><p>Python has positioned itself as a highly suitable programming language for data exploration and analysis with its rich ecosystem of libraries such as NumPy, SciPy, pandas, maptplolib, scikit-learn, etc. and interactive visualization environments such as Jupyter notebooks. The ArcGIS Python API follows suite in being your library for comprehensive analyses of geospatial data. With an intuitive design and easy to use syntax, the API opens up access to rich geoprocessing services and big data analysis capabilities of spatial data. </p><p>ArcGIS API for Python is a Python library for working with maps and geospatial data. It provides simple and efficient tools for sophisticated vector and raster analysis, geocoding, map making, routing and directions, as well as for organizing and managing a GIS with users, groups and information items. In addition to working with your own data, the library enables access to ready to use maps and curated geographic data from Esri and other autorotative sources. It also integrates well with the scientific Python ecosystem and includes rich support for Pandas and Jupyter notebook.</p><p>This workshop will cover how analysts and data scientists can use the ArcGIS platform in combination with data science libraries from Python for mapping, visualization and geospatial data analysis. </p><p>A proposed outline of the talk is below:</p><ul><li><strong>Jupyter notebooks for geospatial data science and analysis</strong></li><li><strong>Mapping</strong></li><li>the map widget</li><li>web maps</li><li>3d maps / scenes</li><li><strong>Exploratory data analysis</strong></li><li>Feature and raster layers</li><li>pandas </li><li>spatial dataframe</li><li><strong>Visualization</strong></li><li>matplotlib and bokeh charting</li><li>smart mapping, heatmaps</li><li>hotspots, space time cubes</li><li><strong>Analysis</strong></li><li>Spatial analysis</li><li>GeoAnalytics (big data analysis)</li><li>Raster analysis</li><li>Integration with data science libraries</li><li>Opencv-python and imagery layers</li><li><strong>Machine learning with geospatial data</strong></li><li>Scikit-learn and feature data</li></ul></p><p>Analysts and data scientists can use the ArcGIS API in combination with data science libraries in Python for mapping, visualization and geospatial data analysis.  This live-demo style talk will demonstrate how to perform sophisticated vector and raster analysis, geocoding, map making, routing and directions using a Pythonic API along with Jupyter notebooks and Pandas.</p><p>Python has positioned itself as a highly suitable programming language for data exploration and analysis with its rich ecosystem of libraries such as NumPy, SciPy, pandas, maptplolib, scikit-learn, etc. and interactive visualization environments such as Jupyter notebooks. The ArcGIS Python API follows suite in being your library for comprehensive analyses of geospatial data. With an intuitive design and easy to use syntax, the API opens up access to rich geoprocessing services and big data analysis capabilities of spatial data. </p><p>ArcGIS API for Python is a Python library for working with maps and geospatial data. It provides simple and efficient tools for sophisticated vector and raster analysis, geocoding, map making, routing and directions, as well as for organizing and managing a GIS with users, groups and information items. In addition to working with your own data, the library enables access to ready to use maps and curated geographic data from Esri and other autorotative sources. It also integrates well with the scientific Python ecosystem and includes rich support for Pandas and Jupyter notebook.</p><p>This workshop will cover how analysts and data scientists can use the ArcGIS platform in combination with data science libraries from Python for mapping, visualization and geospatial data analysis. </p><p>A proposed outline of the talk is below:</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><ul><li>Basic Python / programming knowldge</li></ul></p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>https://developers.arcgis.com/python/sample-notebooks/</p><p>https://developers.arcgis.com/python/</p><p>https://github.com/Esri/arcgis-python-api/blob/master/talks/uc2017/ArcGIS%20Python%20API%20for%20Analysts%20and%20Data%20Scientists/ArcGIS%20Python%20API%20for%20Analysts%20and%20Data%20Scientists.ipynb</p></p><p>https://developers.arcgis.com/python/sample-notebooks/</p><p>https://developers.arcgis.com/python/</p><p>https://github.com/Esri/arcgis-python-api/blob/master/talks/uc2017/ArcGIS%20Python%20API%20for%20Analysts%20and%20Data%20Scientists/ArcGIS%20Python%20API%20for%20Analysts%20and%20Data%20Scientists.ipynb</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>Rohit Singh is the lead developer of ArcGIS API for Python, at Esri, the world leader in GIS. </p><p>Rohit graduated from IIT Kharagpur with a degree in Architecture and has extensive experience and passion in the field of software design and development. In a rich career spanning over 18 years, Rohit has worked for large and small companies, including startups as well as global technology behemoths such as IBM and TCS. For the past 15 years, he has worked as a lead software architect at Esri, the world leader in GIS, and been instrumental in the design and development of several industry leading GIS products such as ArcGIS Engine, ArcGIS Enterprise and the ArcGIS API for Python. He frequently presents at conferences around the world, showcasing the latest developments in the field of geospatial analysis and technology.</p></p><p>Rohit Singh is the lead developer of ArcGIS API for Python, at Esri, the world leader in GIS. </p><p>Rohit graduated from IIT Kharagpur with a degree in Architecture and has extensive experience and passion in the field of software design and development. In a rich career spanning over 18 years, Rohit has worked for large and small companies, including startups as well as global technology behemoths such as IBM and TCS. For the past 15 years, he has worked as a lead software architect at Esri, the world leader in GIS, and been instrumental in the design and development of several industry leading GIS products such as ArcGIS Engine, ArcGIS Enterprise and the ArcGIS API for Python. He frequently presents at conferences around the world, showcasing the latest developments in the field of geospatial analysis and technology.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p>https://github.com/rohitgeo</p></p><p>https://github.com/rohitgeo</p>",
            "date": "07 Aug, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/geospatial-data-science-and-analysis-using-arcgis-api-for-python~eZp8b/",
            "speaker": {
                "name": "Rohit Singh (~rohitgeo)",
                "info": "",
                "photo": ""
            }
        },
        "100": {
            "title": "Scientific computing using Cython: Best of both worlds!",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>Cython is not only an excellent and widely used tool to speed up computational Python code, it\u2019s also a very smart way to talk to native code and libraries. The Cython compiler translates Python code to C or C++ code, and supports static type annotations to allow direct use of C/C++ data types and functions. You get the best of both worlds while working with Cython: Python like syntax with blazing fast C speed.</p><p>This talk/tutorial by a Python/Cython developer introduces Cython programming language and leads the participants all the way from their first Python extension to an efficient integration with native C. Topics covered will be: 1. Using the Cython compiler to build a native extension module 2. Cython development from Jupyter notebook 3. Mixing Python with static C types in the Cython language 4. Calling into native code from Cython code (Brief introduction) 5. Wrap up: A brief case study Cyvlfeat: A Cython/Python wrapper for Computer Vision library, VLFeat.</p><p>Participants are expected to have a good understanding of the Python language, some basic knowledge about C or C++. No deep C programming knowledge is required, nor is any prior knowledge needed about writing extension modules for the CPython runtime.</p></p><p>Cython is not only an excellent and widely used tool to speed up computational Python code, it\u2019s also a very smart way to talk to native code and libraries. The Cython compiler translates Python code to C or C++ code, and supports static type annotations to allow direct use of C/C++ data types and functions. You get the best of both worlds while working with Cython: Python like syntax with blazing fast C speed.</p><p>This talk/tutorial by a Python/Cython developer introduces Cython programming language and leads the participants all the way from their first Python extension to an efficient integration with native C. Topics covered will be: 1. Using the Cython compiler to build a native extension module 2. Cython development from Jupyter notebook 3. Mixing Python with static C types in the Cython language 4. Calling into native code from Cython code (Brief introduction) 5. Wrap up: A brief case study Cyvlfeat: A Cython/Python wrapper for Computer Vision library, VLFeat.</p><p>Participants are expected to have a good understanding of the Python language, some basic knowledge about C or C++. No deep C programming knowledge is required, nor is any prior knowledge needed about writing extension modules for the CPython runtime.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><p>Participants should be familiar with Python syntax and C syntax (Optional).</p></p><p>Participants should be familiar with Python syntax and C syntax (Optional).</p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>https://github.com/simmimourya1/europython17</p></p><p>https://github.com/simmimourya1/europython17</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>Simmi Mourya is on a mission to promote the Python programming language to facilitate the growth of a diverse community of Python Ninjas. She is a deep learning engineer at Predible Health. Her interest lies in Deep Learning and Artificial Intelligence. She is about to finish Udacity's Artificial Intelligence Nano-degree. She has a good amount of experience in Cython programming language because of her contributions to Cyvlfeat, a Cython/Python wrapper for famous Computer Vision library named VLFeat. Find it here: https://github.com/menpo/cyvlfeat She has a lot of speaking experience. She's an active speaker at Women Tech Makers Delhi, India. Previously, she has presented at Europython 2017, Fossasia Open Tech Summit 2017, Singapore. She is a past Google Summer of Code scholar. She has also provided mentoring support for Google Code-In 2016. You can find her stargazing almost every night! She loves photography and singing. She makes the best pasta!</p></p><p>Simmi Mourya is on a mission to promote the Python programming language to facilitate the growth of a diverse community of Python Ninjas. She is a deep learning engineer at Predible Health. Her interest lies in Deep Learning and Artificial Intelligence. She is about to finish Udacity's Artificial Intelligence Nano-degree. She has a good amount of experience in Cython programming language because of her contributions to Cyvlfeat, a Cython/Python wrapper for famous Computer Vision library named VLFeat. Find it here: https://github.com/menpo/cyvlfeat She has a lot of speaking experience. She's an active speaker at Women Tech Makers Delhi, India. Previously, she has presented at Europython 2017, Fossasia Open Tech Summit 2017, Singapore. She is a past Google Summer of Code scholar. She has also provided mentoring support for Google Code-In 2016. You can find her stargazing almost every night! She loves photography and singing. She makes the best pasta!</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p>https://github.com/simmimourya1https://gsoc2016.wordpress.com</p></p><p>https://github.com/simmimourya1https://gsoc2016.wordpress.com</p>",
            "date": "05 Aug, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/scientific-computing-using-cython-best-of-both-worlds~aO5Qd/",
            "speaker": {
                "name": "Simmi Mourya (~simmimourya1)",
                "info": "",
                "photo": ""
            }
        },
        "106": {
            "title": "Visualizing machine learning algorithms in Python",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>Machine learning algorithms are increasingly black-box models. However, their outputs are business data that humans need to understand and act upon.</p><p>For example, if a clustering model suggests 4 customer clusters, how do we identify and characterize these? If a random forest model suggests a pattern of classification, how do we understand the dominant factors and the irrelevant ones?</p><p>These topics fall under the umbrella of model visualization -- where the inputs, process and output of machine learning models are the topic of understanding.</p><p>This talk explores some of the prevalent ways of visualizing machine learning models.</p></p><p>Machine learning algorithms are increasingly black-box models. However, their outputs are business data that humans need to understand and act upon.</p><p>For example, if a clustering model suggests 4 customer clusters, how do we identify and characterize these? If a random forest model suggests a pattern of classification, how do we understand the dominant factors and the irrelevant ones?</p><p>These topics fall under the umbrella of model visualization -- where the inputs, process and output of machine learning models are the topic of understanding.</p><p>This talk explores some of the prevalent ways of visualizing machine learning models.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><p>A basic understanding of ML models</p></p><p>A basic understanding of ML models</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>Anand is a co-founder of Gramener, a data science company. He leads a team of data enthusiasts with skills in analysis, design, programming and statistics.</p></p><p>Anand is a co-founder of Gramener, a data science company. He leads a team of data enthusiasts with skills in analysis, design, programming and statistics.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><ul><li><a href=\"https://www.youtube.com/playlist?list=PLrn2FHBzHtaOGyyqkShkRsAzBCD7fFBqO\">Videos of previous talks</a></li><li><a href=\"https://www.slideshare.net/gramener\">Slides of previous talks</a></li></ul></p>",
            "date": "03 Aug, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/visualizing-machine-learning-algorithms-in-python~eE64a/",
            "speaker": {
                "name": "Anand S (~anand40)",
                "info": "",
                "photo": ""
            }
        },
        "126": {
            "title": "Scalable Big Data solutions using Lambda Architecture",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>In this digital age, we are generating data at an unprecedented rate. But generating data is not the same as curating knowledge. To extract useful insights from the data and to tame the three Vs of data (Volume, Velocity and Variety), we need to rethink our tools and design principles.</p><p>There are two orthogonal approaches to solve this problem. One approach is where we use a new set of tools: </p><ul><li>NoSQL Databases - Mongo, Cassandra, HBase</li><li>Highly Scalable Message Queues - Kafka</li><li>Distributed filesystems - HDFS</li><li>MapReduce Paradigm - Hadoop, Spark</li></ul><p>The other and more fundamental line of thought is to innovate around the underlying architecture itself.  In this series of innovations and improvement, we have an alternate paradigm for Big Data computation - the Lambda Architecture</p><p><strong>Lambda architecture - a generic, scalable and fault-tolerant data processing architecture</strong> and goes beyond any specific set of tools or libraries. As a concrete example, PySpark provides abstractions which makes it very easy to write big data applications. Alternatively, one may build their own big data application using components like Airflow, PyAkka etc. The idea of this talk is to introduce the architecture itself and make it easy for people to understand and relate to it.</p><p>In this talk we would cover the following aspects :</p><ol><li>Introduction and motivation</li><li>Design philosophy behind Lambda Architecture</li><li>Components</li><li>Pros and Cons</li><li>Applications</li><li>Alternatives to Lambda Architecture</li></ol><p>We would be doing this talk as a dialogue between the two speakers to encourage thought-processing and brainstorming in the audience. In our experience, a conversational setting is more engaging and connectable for the audience.</p><p>The notes for the talk are available at <a href=\"https://github.com/shagunsodhani/Lambda-Architecture\">https://github.com/shagunsodhani/Lambda-Architecture</a></p></p><p>In this digital age, we are generating data at an unprecedented rate. But generating data is not the same as curating knowledge. To extract useful insights from the data and to tame the three Vs of data (Volume, Velocity and Variety), we need to rethink our tools and design principles.</p><p>There are two orthogonal approaches to solve this problem. One approach is where we use a new set of tools: </p><p>The other and more fundamental line of thought is to innovate around the underlying architecture itself.  In this series of innovations and improvement, we have an alternate paradigm for Big Data computation - the Lambda Architecture</p><p><strong>Lambda architecture - a generic, scalable and fault-tolerant data processing architecture</strong> and goes beyond any specific set of tools or libraries. As a concrete example, PySpark provides abstractions which makes it very easy to write big data applications. Alternatively, one may build their own big data application using components like Airflow, PyAkka etc. The idea of this talk is to introduce the architecture itself and make it easy for people to understand and relate to it.</p><p>In this talk we would cover the following aspects :</p><p>We would be doing this talk as a dialogue between the two speakers to encourage thought-processing and brainstorming in the audience. In our experience, a conversational setting is more engaging and connectable for the audience.</p><p>The notes for the talk are available at <a href=\"https://github.com/shagunsodhani/Lambda-Architecture\">https://github.com/shagunsodhani/Lambda-Architecture</a></p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><p>No prerequisites.</p></p><p>No prerequisites.</p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>The presentation (along with detailed explanation) would be soon available. The notes for the talk are available at <a href=\"https://github.com/shagunsodhani/Lambda-Architecture\">https://github.com/shagunsodhani/Lambda-Architecture</a></p></p><p>The presentation (along with detailed explanation) would be soon available. The notes for the talk are available at <a href=\"https://github.com/shagunsodhani/Lambda-Architecture\">https://github.com/shagunsodhani/Lambda-Architecture</a></p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p><strong>Shagun Sodhani</strong></p><p>I am a Machine Learning developer working with the Data Science and Analytics team at Adobe Systems. I have also been a teaching assistant for the 3-course series titled Data Science and Engineering with Spark XSeries, created in partnership with professors from University of California, Berkeley, University of California, Los Angeles and Databricks and offered on the edX platform.</p><p>I have good experience of public speaking and have previously given talks at:</p><ul><li>PyCon 2016</li><li>Big Data Training Program, IIT Roorkee</li></ul><p><strong>Navya Agarwal</strong> </p><p>I am a polyglot developer working with the LiveFyre team at Adobe Systems. I currently look after the authentication and orchestration part of the stack with the broad goal of optimizing the performance and scalability of the system. I am also looking at various language modeling use cases for our product. Over the past 2 years, I have dabbled with multiple tech stacks and have worked on various innovative ideas with different products. Prior to joining Adobe, I have been a DAAD research scholar at Chemnitz University of Technology (Germany) and was a gold medalist at MNNIT. I have also worked in the area of statistical machine translation at IIIT Hyderabad.</p><p>I am also delivering a talk on <strong>Encoder Decoder Systems</strong> at PyDataDelhi Conference in September.</p><p>I have been an active speaker in Adobe and have given tech talks on various topics including:</p><ul><li>Quartz as the core scheduling service for our workflows</li><li>Lambda Expression as the building blocks for our services</li></ul></p><p><strong>Shagun Sodhani</strong></p><p>I am a Machine Learning developer working with the Data Science and Analytics team at Adobe Systems. I have also been a teaching assistant for the 3-course series titled Data Science and Engineering with Spark XSeries, created in partnership with professors from University of California, Berkeley, University of California, Los Angeles and Databricks and offered on the edX platform.</p><p>I have good experience of public speaking and have previously given talks at:</p><p><strong>Navya Agarwal</strong> </p><p>I am a polyglot developer working with the LiveFyre team at Adobe Systems. I currently look after the authentication and orchestration part of the stack with the broad goal of optimizing the performance and scalability of the system. I am also looking at various language modeling use cases for our product. Over the past 2 years, I have dabbled with multiple tech stacks and have worked on various innovative ideas with different products. Prior to joining Adobe, I have been a DAAD research scholar at Chemnitz University of Technology (Germany) and was a gold medalist at MNNIT. I have also worked in the area of statistical machine translation at IIIT Hyderabad.</p><p>I am also delivering a talk on <strong>Encoder Decoder Systems</strong> at PyDataDelhi Conference in September.</p><p>I have been an active speaker in Adobe and have given tech talks on various topics including:</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p><a href=\"https://github.com/shagunsodhani\">@shagunsodhani</a></p><p><a href=\"https://github.com/navagarw\">@navagarw</a></p></p><p><a href=\"https://github.com/shagunsodhani\">@shagunsodhani</a></p><p><a href=\"https://github.com/navagarw\">@navagarw</a></p>",
            "date": "18 Jul, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/scalable-big-data-solutions-using-lambda-architecture~elM7a/",
            "speaker": {
                "name": "Navya Agarwal (~navya)",
                "info": "",
                "photo": ""
            }
        },
        "129": {
            "title": "Boosting Python Web Applications with Protocol Buffers and GRPC",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p><img alt=\"enter image description here\" src=\"https://image.slidesharecdn.com/microservicessummittalk-1-31-170208170653/95/bringing-learnings-from-googley-microservices-with-grpc-varun-talwar-google-42-638.jpg?cb=1486576122\"/></p><p>Do you know in the current micro services world, how to spot the critical parts of a monolith and replace them with modern efficient technologies? Have you ever wondered how Google or Netflix scale their traffic? For all these questions you should know how you can boost your web applications using Protocol Buffers and GRPC. Protocol Buffer is the data format that allows you to efficiently compose and read messages in binary format over HTTP/2. GRPC is a transport mechanism which delivers the protocol buffers over the wire. In the recent days, businesses may integrate with third party systems. For that to be smooth, any system can implement a micro service and others can consume it and vice versa.</p></p><p><img alt=\"enter image description here\" src=\"https://image.slidesharecdn.com/microservicessummittalk-1-31-170208170653/95/bringing-learnings-from-googley-microservices-with-grpc-varun-talwar-google-42-638.jpg?cb=1486576122\"/></p><p>Do you know in the current micro services world, how to spot the critical parts of a monolith and replace them with modern efficient technologies? Have you ever wondered how Google or Netflix scale their traffic? For all these questions you should know how you can boost your web applications using Protocol Buffers and GRPC. Protocol Buffer is the data format that allows you to efficiently compose and read messages in binary format over HTTP/2. GRPC is a transport mechanism which delivers the protocol buffers over the wire. In the recent days, businesses may integrate with third party systems. For that to be smooth, any system can implement a micro service and others can consume it and vice versa.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><p>Knowledge of JSON based REST services. Others will be covered in the talk.</p></p><p>Knowledge of JSON based REST services. Others will be covered in the talk.</p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>Talk's preliminary  slides are here:</p><p><a href=\"https://goo.gl/bb1RDh\">https://goo.gl/bb1RDh</a></p></p><p>Talk's preliminary  slides are here:</p><p><a href=\"https://goo.gl/bb1RDh\">https://goo.gl/bb1RDh</a></p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p><img alt=\"enter image description here\" src=\"https://challengepost-s3-challengepost.netdna-ssl.com/photos/production/user_photos/000/263/747/datas/profile.JPG\"/></p><p>Naren Arya, currently working as Software Engineer 2  at Citrix R&amp;D, India. He is a Pythonista from the beginning. Currently joined the cloud services team in Citrix in a full stack development role. He is well known with his Python blog Impythonist. Gave many conference talks and presentations before. He is willing to share his knowledge of building micro services  with Protocol Buffers &amp; GRPC. Naren previously worked at few innovative startups like Knowlarity Cloud Telephony for integrating many different platforms using Django &amp; BackboneJS.</p><p>He loves blogging on open source because it is the simplest way to explain things to the loving community. Apart from Python, he loves web development overall, best practices of scaling etc.</p></p><p><img alt=\"enter image description here\" src=\"https://challengepost-s3-challengepost.netdna-ssl.com/photos/production/user_photos/000/263/747/datas/profile.JPG\"/></p><p>Naren Arya, currently working as Software Engineer 2  at Citrix R&amp;D, India. He is a Pythonista from the beginning. Currently joined the cloud services team in Citrix in a full stack development role. He is well known with his Python blog Impythonist. Gave many conference talks and presentations before. He is willing to share his knowledge of building micro services  with Protocol Buffers &amp; GRPC. Naren previously worked at few innovative startups like Knowlarity Cloud Telephony for integrating many different platforms using Django &amp; BackboneJS.</p><p>He loves blogging on open source because it is the simplest way to explain things to the loving community. Apart from Python, he loves web development overall, best practices of scaling etc.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p><a href=\"https://github.com/narenaryan\">https://github.com/narenaryan</a></p><p><a href=\"https://www.linkedin.com/in/narenarya/\">https://www.linkedin.com/in/narenarya/</a></p><p><a href=\"https://impythonist.wordpress.com/\">https://impythonist.wordpress.com/</a></p><p><a href=\"https://www.youtube.com/watch?v=NAwFrYcAY8Y\">https://www.youtube.com/watch?v=NAwFrYcAY8Y</a></p><p><a href=\"https://medium.com/@narenarya\">https://medium.com/@narenarya</a></p></p><p><a href=\"https://github.com/narenaryan\">https://github.com/narenaryan</a></p><p><a href=\"https://www.linkedin.com/in/narenarya/\">https://www.linkedin.com/in/narenarya/</a></p><p><a href=\"https://impythonist.wordpress.com/\">https://impythonist.wordpress.com/</a></p><p><a href=\"https://www.youtube.com/watch?v=NAwFrYcAY8Y\">https://www.youtube.com/watch?v=NAwFrYcAY8Y</a></p><p><a href=\"https://medium.com/@narenarya\">https://medium.com/@narenarya</a></p>",
            "date": "16 Jul, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/boosting-python-web-applications-with-protocol-buffers-and-grpc~egQZb/",
            "speaker": {
                "name": "Naren (~narenaryan)",
                "info": "",
                "photo": ""
            }
        },
        "130": {
            "title": "Complex network analysis using NetworkX - Graph Theory in Python",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p><a href=\"https://github.com/networkx/networkx\">NetworkX</a> is a well maintained Python library for the creation, manipulation, and study of graphs and complex networks. NetworkX provides data structures for networks along with graph algorithms, generators, and drawing tools. In particular NetworkX complements Python's scientific computing suite of SciPy/NumPy, Matplotlib, and Graphviz and can handle graphs in very large memory. NetworkX is recommended to be part of every data scientist's toolkit.</p><p>The core algorithms that are included are implemented on very fast legacy code. Graphs are hugely flexible (nodes can be any hashable type), and there is an extensive set of native IO formats.</p><p>The workshop would be focused on the basic usage of NetworkX in manipulation of Graphs. After that, we would show some real scientific usage of NetworkX and deal with one or two implementations right on hand.</p></p><p><a href=\"https://github.com/networkx/networkx\">NetworkX</a> is a well maintained Python library for the creation, manipulation, and study of graphs and complex networks. NetworkX provides data structures for networks along with graph algorithms, generators, and drawing tools. In particular NetworkX complements Python's scientific computing suite of SciPy/NumPy, Matplotlib, and Graphviz and can handle graphs in very large memory. NetworkX is recommended to be part of every data scientist's toolkit.</p><p>The core algorithms that are included are implemented on very fast legacy code. Graphs are hugely flexible (nodes can be any hashable type), and there is an extensive set of native IO formats.</p><p>The workshop would be focused on the basic usage of NetworkX in manipulation of Graphs. After that, we would show some real scientific usage of NetworkX and deal with one or two implementations right on hand.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><ul><li>Beginner-level familiarity with Graphs</li></ul></p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><ul><li><a href=\"https://github.com/OrkoHunter/notebooks/tree/master/NetworkX\">Notebooks used at SciPy India 2015 and VPCOE (University of Pune) tutorials on NetworkX</a></li><li><a href=\"https://docs.google.com/presentation/d/1KrrG5ZZt9ShS7KFptAwYWogzuG1MWs01Bj4fV-7XN4Q/edit?usp=sharing\">Slides used at SciPy India 2015</a></li><li><a href=\"https://github.com/networkx/networkx\">NetworkX Repository</a></li><li><a href=\"https://github.com/networkx/notebooks\">NetworkX notebooks</a></li></ul></p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>I (Himanshu Mishra) am a fourth year undergrad student at IIT Kharagpur pursuing Mathematics and Computing. I have worked on NetworkX as a <a href=\"https://www.google-melange.com/gsoc/project/details/google/gsoc2015/orkohunter/5707702298738688\">Google Summer of Code 2015</a> student. I am currently a GSoC 2017 mentor under Python Software Foundation (Timelab) where I was a <a href=\"https://summerofcode.withgoogle.com/archive/2016/projects/4644645548064768/\">GSoC 2016</a> student.</p><p>I am passionate about Software and Python.</p></p><p>I (Himanshu Mishra) am a fourth year undergrad student at IIT Kharagpur pursuing Mathematics and Computing. I have worked on NetworkX as a <a href=\"https://www.google-melange.com/gsoc/project/details/google/gsoc2015/orkohunter/5707702298738688\">Google Summer of Code 2015</a> student. I am currently a GSoC 2017 mentor under Python Software Foundation (Timelab) where I was a <a href=\"https://summerofcode.withgoogle.com/archive/2016/projects/4644645548064768/\">GSoC 2016</a> student.</p><p>I am passionate about Software and Python.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><ul><li><a href=\"https://github.com/OrkoHunter\">GitHub</a></li><li><a href=\"https://orkohunter.net\">Website</a></li><li><a href=\"https://medium.com/@OrkoHunter\">Blog</a></li><li><a href=\"https://youtu.be/7tcJi378B2M\">Talk at SciPy 2017, Austin TX</a></li></ul></p>",
            "date": "15 Jul, 2017",
            "type": "workshop",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/complex-network-analysis-using-networkx-graph-theory-in-python~e0XVe/",
            "speaker": {
                "name": "Himanshu Mishra (~OrkoHunter)",
                "info": "",
                "photo": ""
            }
        },
        "135": {
            "title": "Effectively Debugging Deep Neural Networks",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>Deep learning is expensive. Not only is there a steep (human) learning curve, there is also an immense cost in designing and training a deep neural network. In typical R&amp;D settings, it is very common for a deep network to take days to train. To make things even more tough, there are no guarantees of convergence. It is not uncommon to find that a network has learnt nothing even after hours or even days of training. And it is likely that we as practitioners, too, might not learn much from the experience. The worst possible way to deal with an untrainable network is to leave it alone (apart from a few minor tweaks like changing the learning rate or picking a different training subset of the data) and let it run for another few hours or days.</p><p>Python is known best to be a language that allows you to do rapid prototyping. But even this feature is at its least impressive when it comes to deep learning (understandably so, since Python is just the top layer in most deep learning frameworks). Nevertheless, there are many techniques one can employ to help improve feedback from the network, and even to fail fast, thereby saving precious time.</p><p>While no algorithm or technique can guarantee whether a network will learn anything to a specified degree, there are many practices we can use to be relatively more confident about the performance of the network, as against being totally in the dark. One should be able to say with some confidence, things of this sort:</p><blockquote><p>\"The loss should have dropped below X by now.\"</p><p>\"It should have learnt to classify at least the second category from the rest.\"</p><p>\"It should clearly not be taking so long to converge.\"</p></blockquote><p>This is an advanced workshop intended to make users comfortable with debugging deep networks.</p></p><p>Deep learning is expensive. Not only is there a steep (human) learning curve, there is also an immense cost in designing and training a deep neural network. In typical R&amp;D settings, it is very common for a deep network to take days to train. To make things even more tough, there are no guarantees of convergence. It is not uncommon to find that a network has learnt nothing even after hours or even days of training. And it is likely that we as practitioners, too, might not learn much from the experience. The worst possible way to deal with an untrainable network is to leave it alone (apart from a few minor tweaks like changing the learning rate or picking a different training subset of the data) and let it run for another few hours or days.</p><p>Python is known best to be a language that allows you to do rapid prototyping. But even this feature is at its least impressive when it comes to deep learning (understandably so, since Python is just the top layer in most deep learning frameworks). Nevertheless, there are many techniques one can employ to help improve feedback from the network, and even to fail fast, thereby saving precious time.</p><p>While no algorithm or technique can guarantee whether a network will learn anything to a specified degree, there are many practices we can use to be relatively more confident about the performance of the network, as against being totally in the dark. One should be able to say with some confidence, things of this sort:</p><p>\"The loss should have dropped below X by now.\"</p><p>\"It should have learnt to classify at least the second category from the rest.\"</p><p>\"It should clearly not be taking so long to converge.\"</p><p>This is an advanced workshop intended to make users comfortable with debugging deep networks.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><ul><li>Basics of neural networks: The audiences should know what the different hyperparameters of neural networks are, especially learning rate, gradient optimizers, regularization methods etc. We will be learning how to pick the correct combination of these for a specific problem.</li><li>Entry-level experience with keras</li><li>Basics of either one of tensorflow of theano</li><li>A laptop with a at least a quad-core processor (you should see four cores when you open the Task Manager or htop) and and at least 4GB memory.</li></ul></p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>In progress.</p></p><p>In progress.</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>I am a data scientist based in New Delhi. I currently work as the Practice Lead, Data Science at Juxt Smartmandate Analytical Solutions Pvt Ltd. I am an active member of the Python community. I've spoken at various conferences about my FOSS work. My research interests are in signal processing and machine learning. In my spare time I like to dabble with applications of machine learning in personal productivity.</p></p><p>I am a data scientist based in New Delhi. I currently work as the Practice Lead, Data Science at Juxt Smartmandate Analytical Solutions Pvt Ltd. I am an active member of the Python community. I've spoken at various conferences about my FOSS work. My research interests are in signal processing and machine learning. In my spare time I like to dabble with applications of machine learning in personal productivity.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p><a href=\"https://jaidevd.github.io\"><img alt=\"\" src=\"https://image.flaticon.com/icons/png/128/12/12195.png\"/></a> <a href=\"https://twitter.com/jaidevd\"><img alt=\"\" src=\"https://cdn1.iconfinder.com/data/icons/logotypes/32/twitter-128.png\"/></a> <a href=\"https://github.com/jaidevd\"><img alt=\"\" src=\"https://cdn0.iconfinder.com/data/icons/octicons/1024/mark-github-128.png\"/></a></p></p><p><a href=\"https://jaidevd.github.io\"><img alt=\"\" src=\"https://image.flaticon.com/icons/png/128/12/12195.png\"/></a> <a href=\"https://twitter.com/jaidevd\"><img alt=\"\" src=\"https://cdn1.iconfinder.com/data/icons/logotypes/32/twitter-128.png\"/></a> <a href=\"https://github.com/jaidevd\"><img alt=\"\" src=\"https://cdn0.iconfinder.com/data/icons/octicons/1024/mark-github-128.png\"/></a></p>",
            "date": "12 Jul, 2017",
            "type": "workshop",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/effectively-debugging-deep-neural-networks~e3Y4b/",
            "speaker": {
                "name": "Jaidev Deshpande (~jaidev)",
                "info": "",
                "photo": ""
            }
        },
        "141": {
            "title": "Python for Data Analysis",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>Typically it takes 60 to 80% of the time to collect required data, cleanse it and analyse in any data science project. It is very essential for one to be familiar with various tools/libraries available in python for doing data analysis and understanding the data.  This hands on workshop's objective is to provide overview of the libraries and how to use them for various activities performed during the data analysis</p><p>Following will be covered as part of this session</p><ul><li>How does data analysis fit in the life cycle of data science project</li><li>Dealing with numpy arrays</li><li>Reading data using various formats, dealing with missing values</li><li>Using pandas plot features to visualize and understand the data</li><li>Analyzing one of the open source data set</li></ul><p>By the end of the session, audience will have very good understanding of how to apply numpy, pandas to analyze, understand and prepare data set required for starting machine learning</p></p><p>Typically it takes 60 to 80% of the time to collect required data, cleanse it and analyse in any data science project. It is very essential for one to be familiar with various tools/libraries available in python for doing data analysis and understanding the data.  This hands on workshop's objective is to provide overview of the libraries and how to use them for various activities performed during the data analysis</p><p>Following will be covered as part of this session</p><p>By the end of the session, audience will have very good understanding of how to apply numpy, pandas to analyze, understand and prepare data set required for starting machine learning</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><p>Hands on exposure with basic python programming language</p></p><p>Hands on exposure with basic python programming language</p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>https://github.com/sdonapar/python_training </p><p>https://github.com/sdonapar/data_analysis_made_easy</p></p><p>https://github.com/sdonapar/python_training </p><p>https://github.com/sdonapar/data_analysis_made_easy</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 5 years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving/automating the same. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib).</p></p><p>I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 5 years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving/automating the same. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib).</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p>github link - https://github.com/sdonapar</p><p>linkedin profile - https://www.linkedin.com/in/sasidonaparthi</p><p>twitter handle - <strong>@sdonapar</strong></p></p><p>github link - https://github.com/sdonapar</p><p>linkedin profile - https://www.linkedin.com/in/sasidonaparthi</p><p>twitter handle - <strong>@sdonapar</strong></p>",
            "date": "10 Jul, 2017",
            "type": "workshop",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/python-for-data-analysis~eVJBe/",
            "speaker": {
                "name": "Sasidhar Donaparthi (~sasidhar)",
                "info": "",
                "photo": ""
            }
        },
        "142": {
            "title": "Security lessons learned from building serverless systems",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>Serverless systems are systems where servers need not be running and being maintained round the clock. The paradigm uses functions and the concept of containerization to spawn on-demand light-weight containers for executing a task, and safely destroying the server when the task is completed.</p><p>As this is a new domain, the practices and concepts of ensuring security and doing the logging and monitoring, are still mostly difficult and not-fully-solved problems.</p><p>This talk stresses upon the security part of serverless systems explaining the lessons learned and pitfalls experienced from building distributed, serverless systems. </p><p>[Will be using AWS-specific examples whenever a tool-related point arises. But, that should fairly generalize to other cloud providers too.]</p></p><p>Serverless systems are systems where servers need not be running and being maintained round the clock. The paradigm uses functions and the concept of containerization to spawn on-demand light-weight containers for executing a task, and safely destroying the server when the task is completed.</p><p>As this is a new domain, the practices and concepts of ensuring security and doing the logging and monitoring, are still mostly difficult and not-fully-solved problems.</p><p>This talk stresses upon the security part of serverless systems explaining the lessons learned and pitfalls experienced from building distributed, serverless systems. </p><p>[Will be using AWS-specific examples whenever a tool-related point arises. But, that should fairly generalize to other cloud providers too.]</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>Raj works as a Senior Data Scientist.</p><p>His job includes building ML algorithms, architecting data pipelines, making systems 1% more intelligent,  staring at endless Linux logs and building the devops team.</p><p>Raj is the author of the Julialang cookbook, and is also moderates the DevOps site of StackOverflow</p></p><p>Raj works as a Senior Data Scientist.</p><p>His job includes building ML algorithms, architecting data pipelines, making systems 1% more intelligent,  staring at endless Linux logs and building the devops team.</p><p>Raj is the author of the Julialang cookbook, and is also moderates the DevOps site of StackOverflow</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p>Github: https://github.com/Dawny33</p><p>LinkedIn: https://www.linkedin.com/in/jalemrajrohit/</p><p>Slideshare: https://speakerdeck.com/dawny33</p></p><p>Github: https://github.com/Dawny33</p><p>LinkedIn: https://www.linkedin.com/in/jalemrajrohit/</p><p>Slideshare: https://speakerdeck.com/dawny33</p>",
            "date": "08 Jul, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/security-lessons-learned-from-building-serverless-systems~aQAMa/",
            "speaker": {
                "name": "Jalem Raj Rohit (~Dawny33)",
                "info": "",
                "photo": ""
            }
        },
        "144": {
            "title": "Getting Started with Embedded Python: MicroPython and CircuitPython",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>The <strong>MicroPython</strong> project is an open source implementation of Python 3 that includes a small subset of the Python standard libraries, and is optimised to run on microcontrollers with constrained environments like limited ROM, RAM and processing power. It came to life after a successful Kick-starter campaign by Damien George. CircuitPython is a fork of MicroPython further developed by Adafruit Industries(https://www.adafruit.com) which includes great extension to control analog sensors, RGB and neopixel LEDs etc.</p><p>Traditionally Microcontrollers like AVR, ARM, ESP8266(WiFi SoC) are programmed in Embedded C or Assembly which has a quite overwhelming learning curve, MicroPython makes it easy and allows you to do same with your favourite scripting language Python. Imagine you want to read a sensor or turn on lights from a web server, now you don't need to learn register level programming for that, you can do that with MicroPython, It is also supported on 5$ WiFi SoC, the ESP8266 which is great for making small IoT devices.</p><p>MicroPython is packed full of advanced features such as an interactive prompt, arbitrary precision integers, closures, list comprehension, generators, exception handling and more. Yet it is compact enough to fit and run within just 256k of code space and 16k of RAM.</p><p>MicroPython aims to be as compatible with normal Python as possible to allow you to transfer code with ease from the desktop to a microcontroller or embedded system. You get an interactive prompt (the REPL) to execute commands immediately, along with the ability to run and import scripts from the built-in filesystem. The REPL has history, tab completion, auto-indent and paste mode for a great user experience.</p></p><p>The <strong>MicroPython</strong> project is an open source implementation of Python 3 that includes a small subset of the Python standard libraries, and is optimised to run on microcontrollers with constrained environments like limited ROM, RAM and processing power. It came to life after a successful Kick-starter campaign by Damien George. CircuitPython is a fork of MicroPython further developed by Adafruit Industries(https://www.adafruit.com) which includes great extension to control analog sensors, RGB and neopixel LEDs etc.</p><p>Traditionally Microcontrollers like AVR, ARM, ESP8266(WiFi SoC) are programmed in Embedded C or Assembly which has a quite overwhelming learning curve, MicroPython makes it easy and allows you to do same with your favourite scripting language Python. Imagine you want to read a sensor or turn on lights from a web server, now you don't need to learn register level programming for that, you can do that with MicroPython, It is also supported on 5$ WiFi SoC, the ESP8266 which is great for making small IoT devices.</p><p>MicroPython is packed full of advanced features such as an interactive prompt, arbitrary precision integers, closures, list comprehension, generators, exception handling and more. Yet it is compact enough to fit and run within just 256k of code space and 16k of RAM.</p><p>MicroPython aims to be as compatible with normal Python as possible to allow you to transfer code with ease from the desktop to a microcontroller or embedded system. You get an interactive prompt (the REPL) to execute commands immediately, along with the ability to run and import scripts from the built-in filesystem. The REPL has history, tab completion, auto-indent and paste mode for a great user experience.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><ul><li>Basic Python programming language.</li><li>Basic understanding of processors and programming paradigm.</li><li>Basic command line exposure.</li></ul></p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>My article on \"Getting Started with MicroPython\" was published in:</p><ul><li><p>Open Source for you Magazine - Feb 2017Link: <a href=\"http://opensourceforu.com/2017/03/an-introduction-to-micropython/\">An Introduction to MicroPython</a></p></li><li><p>Electronics for you Magazine - May 2017</p></li></ul><p><a href=\"https://www.slideshare.net/AyanPahwa1/pyconindia2017micropythonayan\">Link to the presentation</a></p></p><p>My article on \"Getting Started with MicroPython\" was published in:</p><p>Open Source for you Magazine - Feb 2017Link: <a href=\"http://opensourceforu.com/2017/03/an-introduction-to-micropython/\">An Introduction to MicroPython</a></p><p>Electronics for you Magazine - May 2017</p><p><a href=\"https://www.slideshare.net/AyanPahwa1/pyconindia2017micropythonayan\">Link to the presentation</a></p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>I am working as an Embedded Software Engineer at Mentor Graphics- A Siemens Business in Noida facility, working mainly on customised Linux kernel and user land environment for Embedded Automotive Solutions like In-Vehicle-Infotainment(IVI) and Advanced Driver Assistance Systems(ADAS). </p><p>Apart from that I am an IoT, Wearable Electronics and Artificial Intelligent enthusiasts, managing operations in same for an IoT startup(http://sdiot.in). I like to code and make DIY projects for fun or automating things. I am a regular blogger for various communities and blog sites. I do lots of open source contribution in various projects ranging from Home Automations to Drone technologies to Embedded libraries.</p><p>I am also among few FPV drone racing pilot from India, member of Indian Drone Racing League <a href=\"http://droneracingindia.com\">IDRL</a>. I've organised various workshops, meet ups and drone air shows in Delhi/NCR on Drone technologies, Python programming language, Linux bash scripting, Github, Contributing in open source, Microcontrollers etc, in companies, colleges and meet up groups.</p></p><p>I am working as an Embedded Software Engineer at Mentor Graphics- A Siemens Business in Noida facility, working mainly on customised Linux kernel and user land environment for Embedded Automotive Solutions like In-Vehicle-Infotainment(IVI) and Advanced Driver Assistance Systems(ADAS). </p><p>Apart from that I am an IoT, Wearable Electronics and Artificial Intelligent enthusiasts, managing operations in same for an IoT startup(http://sdiot.in). I like to code and make DIY projects for fun or automating things. I am a regular blogger for various communities and blog sites. I do lots of open source contribution in various projects ranging from Home Automations to Drone technologies to Embedded libraries.</p><p>I am also among few FPV drone racing pilot from India, member of Indian Drone Racing League <a href=\"http://droneracingindia.com\">IDRL</a>. I've organised various workshops, meet ups and drone air shows in Delhi/NCR on Drone technologies, Python programming language, Linux bash scripting, Github, Contributing in open source, Microcontrollers etc, in companies, colleges and meet up groups.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><ul><li><a href=\"https://iayanpahwa.github.io\"><strong>Website</strong></a></li><li><a href=\"https://www.github.com/iayanpahwa\"><strong>Github</strong></a></li><li><a href=\"https://www.youtube.com/channel/UCgz03WhmWF3otcwXd38bQ9g\"><strong>Youtube</strong></a></li><li><a href=\"https://www.twitter.com/iAyanPahwa\"><strong>Twitter</strong></a></li><li><a href=\"https://www.mentor.com/tannereda/blog/post/securing-iot-devices-2fb40c65-7b7e-4f73-a4c2-89d45b843bfc\"><strong>Blog on security</strong></a></li><li><a href=\"http://opensourceforu.com/2017/03/an-introduction-to-micropython/\"><strong>MicroPython article in open source for you magazine- Feb 2017 edition</strong></a></li></ul></p>",
            "date": "07 Jul, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/getting-started-with-embedded-python-micropython-and-circuitpython~dN7me/",
            "speaker": {
                "name": "Ayan Pahwa (~iayanpahwa)",
                "info": "",
                "photo": ""
            }
        },
        "148": {
            "title": "Empowering African students with Python",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>Python has over the years been generally accepted as the best language for the academic field.  It has been in so many articles, reports and researches recommended as the best starting point for students of all ages. Tools like raspberry Pi, MicroBit have also been built to aid creativity and knowledge retention among young students.Despite these feets and advancements, it\u2019s quite unfortunate that students in Africa are not actively being kept or empowered enough to enjoy some of these features and as such , it is safe to say  the  aforementioned researches focus their study case on countries outside Africa.To help increase the awareness of Python into the African Educational Sector, I started a community of Python Student Enthusiasts. This community called the Python Club is made up of student tech enthusiasts, python programmers,students of various disciplines.It started a year back with just 3 members and is as of now made up of 50 active members from different tertiary schools across Nigeria.This talk was born out of the need to share the many advantages I and the (student) community around me has derived through the use of Python as a tool not only for development but also for educational transformation tool.</p><p>This talk would center around the journey of Python Club from inception, challenges faced, challenges still being faced, success stories,  the eventual aim and everything relating to the community.It will also cover our attempts at getting other African students involved and attempt to launch a student community in one Zimbabwean tertiary schools.</p><p>The talk is open to anyone regardless of their level of Python knowledge.</p></p><p>Python has over the years been generally accepted as the best language for the academic field.  It has been in so many articles, reports and researches recommended as the best starting point for students of all ages. Tools like raspberry Pi, MicroBit have also been built to aid creativity and knowledge retention among young students.Despite these feets and advancements, it\u2019s quite unfortunate that students in Africa are not actively being kept or empowered enough to enjoy some of these features and as such , it is safe to say  the  aforementioned researches focus their study case on countries outside Africa.To help increase the awareness of Python into the African Educational Sector, I started a community of Python Student Enthusiasts. This community called the Python Club is made up of student tech enthusiasts, python programmers,students of various disciplines.It started a year back with just 3 members and is as of now made up of 50 active members from different tertiary schools across Nigeria.This talk was born out of the need to share the many advantages I and the (student) community around me has derived through the use of Python as a tool not only for development but also for educational transformation tool.</p><p>This talk would center around the journey of Python Club from inception, challenges faced, challenges still being faced, success stories,  the eventual aim and everything relating to the community.It will also cover our attempts at getting other African students involved and attempt to launch a student community in one Zimbabwean tertiary schools.</p><p>The talk is open to anyone regardless of their level of Python knowledge.</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>I am an Engineering Student of the Obafemi Awolowo University in Ile-Ife, Nigeria who has a huge interest in Python. I am an active member of the Python Community in Nigeria and I head the Python Community in my school. I have organized, coached at and helped a lot of female (as well as male ) students get familiar with Python using the DjangoGirls events in my school and others.I have used Python in both academic and non-academic ways and as such I can say I have a very good experience and knowledge of it.Aside, being a student, I work at Terragon Group as a DevOps Engineer and as a Student Django Mentor at Code Institute. I also lead the Python Team in Ilab.</p></p><p>I am an Engineering Student of the Obafemi Awolowo University in Ile-Ife, Nigeria who has a huge interest in Python. I am an active member of the Python Community in Nigeria and I head the Python Community in my school. I have organized, coached at and helped a lot of female (as well as male ) students get familiar with Python using the DjangoGirls events in my school and others.I have used Python in both academic and non-academic ways and as such I can say I have a very good experience and knowledge of it.Aside, being a student, I work at Terragon Group as a DevOps Engineer and as a Student Django Mentor at Code Institute. I also lead the Python Team in Ilab.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p>https://github.com/olamyy</p></p><p>https://github.com/olamyy</p>",
            "date": "04 Jul, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/empowering-african-students-with-python~eEKmb/",
            "speaker": {
                "name": "Olamilekan Wahab (~Olamyy)",
                "info": "",
                "photo": ""
            }
        },
        "152": {
            "title": "Walkthrough cpython 3.6 source code",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>This talk will be an introduction to cpython from a source code level. We will walk through the source code of python from the parser, compiler, assembler and interpreter phases. We will also understand the design of the garbage collector, memory allocator from a source code perspective. We shall also explore the different design philosophies of cpython. There will be special emphasis on python objects such as lists, tuples, dictionaries etc and their design internals. This talk is for people who are interested to explore how cpython works internally.</p></p><p>This talk will be an introduction to cpython from a source code level. We will walk through the source code of python from the parser, compiler, assembler and interpreter phases. We will also understand the design of the garbage collector, memory allocator from a source code perspective. We shall also explore the different design philosophies of cpython. There will be special emphasis on python objects such as lists, tuples, dictionaries etc and their design internals. This talk is for people who are interested to explore how cpython works internally.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><ol><li>Python source code.</li><li>gdb</li><li>eclipse latest version</li><li>linux</li><li>make</li></ol></p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>Please read the books available for free download from </p><p><a href=\"http://intopython.com\">http://intopython.com</a></p><p>The books are authored by the same speaker.</p></p><p>Please read the books available for free download from </p><p><a href=\"http://intopython.com\">http://intopython.com</a></p><p>The books are authored by the same speaker.</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>I am Prashanth Raghu and my interest in python began back in 2009 when I was studying at PES University, Bangalore. I used python as a part of my internship project in my final year. It was used to develop a hybrid cloud app with the web front end designed in PHP and monitoring and load testing on python. I was a Google Summer of Code scholar for the year 2014. ( My work: https://github.com/openstack/zaqar/tree/master/zaqar/storage/redis ).</p><p>I studied at National University of Singapore and did my Masters in Wireless Computation with a research paper between 2013-2014. I was struck by a rare disease called Steven Johnson Syndrome in 2015 due to this my startup failed. At this crucial time I decided to do something of my interest  and opened up the source code of python 2.7. I was amazed at the simplicity yet profoundness of the architecture and decided to share my views with the world. And the result of my efforts for a couple of months has resulted into the book \u201cInternals of Cpython 2.7\u201d and \u201cInternals of Cpython3.6\u201d available as a free download under CC 4.0 license.</p></p><p>I am Prashanth Raghu and my interest in python began back in 2009 when I was studying at PES University, Bangalore. I used python as a part of my internship project in my final year. It was used to develop a hybrid cloud app with the web front end designed in PHP and monitoring and load testing on python. I was a Google Summer of Code scholar for the year 2014. ( My work: https://github.com/openstack/zaqar/tree/master/zaqar/storage/redis ).</p><p>I studied at National University of Singapore and did my Masters in Wireless Computation with a research paper between 2013-2014. I was struck by a rare disease called Steven Johnson Syndrome in 2015 due to this my startup failed. At this crucial time I decided to do something of my interest  and opened up the source code of python 2.7. I was amazed at the simplicity yet profoundness of the architecture and decided to share my views with the world. And the result of my efforts for a couple of months has resulted into the book \u201cInternals of Cpython 2.7\u201d and \u201cInternals of Cpython3.6\u201d available as a free download under CC 4.0 license.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><ul><li><a href=\"https://github.com/openstack/zaqar/tree/master/zaqar/storage/redis\">https://github.com/openstack/zaqar/tree/master/zaqar/storage/redis</a> - My contribution as a part of Google summer of code</li><li><a href=\"http://intopython.com\">http://intopython.com</a> - my technical blog on python source code</li><li><a href=\"https://www.linkedin.com/in/prashanthraghu/\">https://www.linkedin.com/in/prashanthraghu/</a></li><li><a href=\"http://bangalore.python.org.in/blog/2017/06/17/jun-talks/\">http://bangalore.python.org.in/blog/2017/06/17/jun-talks/</a> - Video of my talk at Bangpypers Jun 2017 meetup.  </li></ul></p>",
            "date": "04 Jul, 2017",
            "type": "workshop",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/walkthrough-cpython-36-source-code~azq5e/",
            "speaker": {
                "name": "Prashanth Raghu (~PrashanthRaghu)",
                "info": "",
                "photo": ""
            }
        },
        "153": {
            "title": "How import works in Python",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p><strong>Import  machinery</strong> has been revamped and has been re-written in Python3. Not many of the developers are aware of the internal mechanics of how the import system works and how this can be leveraged for some specific use cases</p><p>This talk will introduce the audience to:</p><ul><li>Evolution of import system in python</li><li>What happens under the hoods when a module/package is imported into Python namespace</li><li>Various hooks available that can be leveraged for customization</li><li>Some of the usecases where this can be leveraged</li></ul><p>After the talk, audience will get a clear idea of how import system is implemented in Python3 and will be able to leverage the hooks available for any future use cases</p></p><p><strong>Import  machinery</strong> has been revamped and has been re-written in Python3. Not many of the developers are aware of the internal mechanics of how the import system works and how this can be leveraged for some specific use cases</p><p>This talk will introduce the audience to:</p><p>After the talk, audience will get a clear idea of how import system is implemented in Python3 and will be able to leverage the hooks available for any future use cases</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><p>Knowledge of python programming, basic understanding of Python modules and Packages, knowledge of python standard library modules like sys, os, etc</p></p><p>Knowledge of python programming, basic understanding of Python modules and Packages, knowledge of python standard library modules like sys, os, etc</p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>https://github.com/sdonapar/how_import_works</p><p>https://github.com/sdonapar/how_import_works/blob/master/how_import_works.pdf</p></p><p>https://github.com/sdonapar/how_import_works</p><p>https://github.com/sdonapar/how_import_works/blob/master/how_import_works.pdf</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as  design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology.  I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 5 years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving/automating the same. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib).</p></p><p>I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as  design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology.  I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 5 years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving/automating the same. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib).</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><p>github link - https://github.com/sdonapar</p><p>linkedin profile - https://www.linkedin.com/in/sasidonaparthi</p><p>twitter handle - <strong>@sdonapar</strong></p></p><p>github link - https://github.com/sdonapar</p><p>linkedin profile - https://www.linkedin.com/in/sasidonaparthi</p><p>twitter handle - <strong>@sdonapar</strong></p>",
            "date": "04 Jul, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/how-import-works-in-python~dypzb/",
            "speaker": {
                "name": "Sasidhar Donaparthi (~sasidhar)",
                "info": "",
                "photo": ""
            }
        },
        "154": {
            "title": "Building single page javascript apps with Django, Graphql, Relay and React!",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>I'm the author of a boilerplate called Reango.</p><p>https://github.com/ncrmro/reango</p><p>It features a GraphQL backend powered by Django. Django then serves a Webpack compiled single page application built using React, Relay.</p><p>It features authentication using JWT tokens and with unit and browser tests.</p><p>I'd like to give a talk on when and how to use such a stack as Reango.</p></p><p>I'm the author of a boilerplate called Reango.</p><p>https://github.com/ncrmro/reango</p><p>It features a GraphQL backend powered by Django. Django then serves a Webpack compiled single page application built using React, Relay.</p><p>It features authentication using JWT tokens and with unit and browser tests.</p><p>I'd like to give a talk on when and how to use such a stack as Reango.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><p>What an API is, the Django ORM, a bit of understanding of the difference between server side and client side rendered front ends.</p></p><p>What an API is, the Django ORM, a bit of understanding of the difference between server side and client side rendered front ends.</p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p><a href=\"https://github.com/ncrmro/reango\" title=\"Reango Github Boilerplate\">Reango Github Boilerplate</a></p><p><a href=\"https://drive.google.com/open?id=0B3Qoff7xwUhnanBEcThrR014NEU\" title=\"Presentation\">Presentation Link</a></p></p><p><a href=\"https://github.com/ncrmro/reango\" title=\"Reango Github Boilerplate\">Reango Github Boilerplate</a></p><p><a href=\"https://drive.google.com/open?id=0B3Qoff7xwUhnanBEcThrR014NEU\" title=\"Presentation\">Presentation Link</a></p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>I grew up in Houston Texas, I've owned and worked as  Software Developer/IT consulting company for the last four years, I'm currently using this stack too In one of my business projects and was also hired to implement the Reango stack for a company in Silicon Valley.</p></p><p>I grew up in Houston Texas, I've owned and worked as  Software Developer/IT consulting company for the last four years, I'm currently using this stack too In one of my business projects and was also hired to implement the Reango stack for a company in Silicon Valley.</p>",
            "date": "04 Jul, 2017",
            "type": "talk",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/building-single-page-javascript-apps-with-django-graphql-relay-and-react~axoze/",
            "speaker": {
                "name": "Nicholas Romero (~ncrmro)",
                "info": "",
                "photo": ""
            }
        },
        "155": {
            "title": "Creating Captive Portal with Tornado and Raspberry Pi",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><h1>Aim of the workshop</h1><ul><li>The aim of the workshop is to give insights about on how to create Captive Portal using Tornado and Raspberry Pi. This workshop will cover the following aspects. </li><li>Creating open hotspot using Python and HostAPD</li><li>Configuring HostAPD on Raspberry Pi</li><li>DHCP Configuration and Management </li><li>Creating Basic App using tornado</li><li>System Process and Runnables</li><li>Hands on Raspberry Pi</li></ul><h1>What is a Captive Portal ?</h1><ul><li>A captive portal is a Web page that the user of a public-access network is obliged to view and interact with before access is granted. Captive portals are typically used by business centers, airports, hotel lobbies, coffee shops, and other venues that offer free Wi-Fi hot spots for Internet users.</li></ul><h2>Advantages of Captive Portal</h2><p>Captive Portals allow for the separation and segregation of guest traffic. This has tons of security benefits including keeping un-trusted users away from confidential resources through network access control policies.</p><ul><li>These portals provide data accounting based on time, date and user. This is a standard feature in guest access. Future access to logs will facilitate administrators to find out certain users and their actions in a corporate network.</li><li>A landing page will serve as a means of identifying your brand as well as a way to boost your marketing message. Companies can take advantage of the virtually limitless potential that captive portals possess to raise brand awareness by utilizing its less obvious abilities.</li><li>Providing free internet services doesn\u2019t mean that you're always providing secure internet service. An accepted usage policy (AUP) on your active portal ensures that users understand just that.</li><li>Some users of a free public wireless network may repeatedly connect, using the network on an almost continuous basis for bandwidth hogging activities like downloading music, videos, or other large files. For them you can provide ample bandwidth throttling. </li></ul><h1>Tornado</h1><ul><li>Tornado is a Python web framework and asynchronous networking library. By using non-blocking network I/O, Tornado can scale to tens of thousands of open connections, making it ideal for long polling, Web-Sockets, and other applications that require a long-lived connection to each user.</li></ul><h2>Insight into IPTABLES</h2><ul><li><p>iptables is a user-space application program that allows a system administrator to configure the tables provided by the Linux kernel firewall (implemented as different Netfilter modules) and the chains and rules it stores.</p></li><li><p>Besides the obvious situations where you might imagine this would be useful, such as blocking long lists of \"bad\" hosts without worry of killing system resources or causing network congestion, IP sets also open up new ways of approaching certain aspects of firewall design and simplify many configuration scenarios.</p></li><li><p><em>IPSET</em> : IP sets are a framework inside the Linux kernel, which can be administered by the ipset utility. Depending on the type, an IP set may store IP addresses, networks, (TCP/UDP) port numbers, MAC addresses, interface names or combinations of them in a way, which ensures lightning speed when matching an entry against a set.</p></li></ul></p><p>Captive Portals allow for the separation and segregation of guest traffic. This has tons of security benefits including keeping un-trusted users away from confidential resources through network access control policies.</p><p>iptables is a user-space application program that allows a system administrator to configure the tables provided by the Linux kernel firewall (implemented as different Netfilter modules) and the chains and rules it stores.</p><p>Besides the obvious situations where you might imagine this would be useful, such as blocking long lists of \"bad\" hosts without worry of killing system resources or causing network congestion, IP sets also open up new ways of approaching certain aspects of firewall design and simplify many configuration scenarios.</p><p><em>IPSET</em> : IP sets are a framework inside the Linux kernel, which can be administered by the ipset utility. Depending on the type, an IP set may store IP addresses, networks, (TCP/UDP) port numbers, MAC addresses, interface names or combinations of them in a way, which ensures lightning speed when matching an entry against a set.</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><h2>Pre-requisite for this talk</h2><ul><li>Basic Idea of IPSET and IPTABLES in Linux</li><li>Basic Idea of Tornado [If not! then don't worry you can check out sample from <a href=\"http://www.tornadoweb.org/en/stable/guide.html\">here</a>. </li><li>Audience can bring their own Rasberry Pi (If they have one) else they can use their own Linux Machine for this workshop. </li><li>For people using their own laptop make sure you have Ubuntu 13.xx + installed on your system</li><li>And finally Hunger for Knowledge!</li></ul></p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><ul><li>https://speakerdeck.com/aniketmaithani/wifi-captive-portal-using-raspberry-pi [Basic] </li><li>Code : will be updated soon.</li></ul></p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>My name is Aniket Maithani. I'll keep this short</p><ul><li>Works @Radiowalla Network Pvt. Ltd</li><li>Handles Development &amp; Dev-Ops</li><li>B.Tech (CS&amp;E) graduate from Amity University, Noida (UP)</li><li>Loves to travel</li><li>Blog during free time</li><li>Cricket Lover</li><li>\"CHAI\" addict</li><li>Plays Guitar too!</li></ul></p><p>My name is Aniket Maithani. I'll keep this short</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><ul><li><a href=\"https://github.com/aniketmaithani\">GitHub</a></li><li><a href=\"https://twitter.com/2aniketmaithani\">Twitter</a></li><li><a href=\"https://fb.com/aniket.maithani\">Facebook</a></li><li><a href=\"https://in.linkedin.com/in/aniketmaithani\">LinkedIn</a></li><li><a href=\"http://www.aniketmaithani.net\">Personal Blog</a></li></ul><h2>Past Speaker @:</h2><ul><li><a href=\"https://www.youtube.com/watch?v=n5xUTcsrRns\">PyDelhi Conference 2017</a></li><li><a href=\"http://www.bvimr.com/News_And_Event_Detail.aspx?nid=42\">BVP-IMR</a></li><li><a href=\"https://github.com/pydelhi/talks/issues/38\">PyDelhi Meetup</a></li><li><a href=\"https://github.com/pydelhi/talks/issues/15\">PyDelhi Meetup</a></li><li><a href=\"https://curiousdtu.wordpress.com/2014/03/24/bootconf-2014/\">OSDC Conference</a></li><li><a href=\"https://www.youtube.com/watch?v=i6vKEo12KfE&amp;t=902s\">Webinar on Basics of GIT</a></li><li><a href=\"https://www.youtube.com/watch?v=mz97xjV2TQM\">Webinar on Property Based Testing</a></li></ul></p>",
            "date": "03 Jul, 2017",
            "type": "workshop",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/creating-captive-portal-with-tornado-and-raspberry-pi~dwngb/",
            "speaker": {
                "name": "Aniket Maithani (~aniket)",
                "info": "",
                "photo": ""
            }
        },
        "157": {
            "title": "Binary Analysis and Exploitation using Python",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>Python now has a lot of interesting libraries that can be used together to do Binary Analysis and exploitation. We'll be using the great capstone engine alongside, pyelftools and pefile to analyse a binary programatically. Analyzing includes getting information in the headers, assembly in the code section, imports, dynamic libraries and lots of other stuff. The second part of the talk will be on Exploitation, where we'll try to exploit a buffer overflow vulnerability on a linux application (with ASLR, Stack Cookies and NX). We'll use pwntools and RopGadget . py to generate an exploit.</p><p>I have written a blog post about how to use pyelftools and capstone engine to reverse a simple elf crackme. Check it out here: http://anee.me/reversing-an-elf/</p></p><p>Python now has a lot of interesting libraries that can be used together to do Binary Analysis and exploitation. We'll be using the great capstone engine alongside, pyelftools and pefile to analyse a binary programatically. Analyzing includes getting information in the headers, assembly in the code section, imports, dynamic libraries and lots of other stuff. The second part of the talk will be on Exploitation, where we'll try to exploit a buffer overflow vulnerability on a linux application (with ASLR, Stack Cookies and NX). We'll use pwntools and RopGadget . py to generate an exploit.</p><p>I have written a blog post about how to use pyelftools and capstone engine to reverse a simple elf crackme. Check it out here: http://anee.me/reversing-an-elf/</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><ul><li>Interest in computer security</li><li>Basic knowledge about ELFs and PE</li><li>Knowledge about buffer overflows</li></ul></p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p><a href=\"https://anee.me/reversing-an-elf-from-the-ground-up-4fe1ec31db4a/\">https://anee.me/reversing-an-elf-from-the-ground-up-4fe1ec31db4a</a></p></p><p><a href=\"https://anee.me/reversing-an-elf-from-the-ground-up-4fe1ec31db4a/\">https://anee.me/reversing-an-elf-from-the-ground-up-4fe1ec31db4a</a></p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>I am a recent CS grad from IIIT Delhi. I am currently working with DirectI as a DevOps engineer. I participate in a lot of CTFs and I love to work with Binaries, trying to understand what they do and how to go about exploiting them. I also have experience in Network Security and anonymity and am currently working on a research project on Decoy Routing. Besides that I really love opensource. I have contributed to a lot of organizations including Libav, KDE, Sugarlabs, Radare2. I have participated in GSoC before and have been winner of Google Code in 2012 and 2011.</p></p><p>I am a recent CS grad from IIIT Delhi. I am currently working with DirectI as a DevOps engineer. I participate in a lot of CTFs and I love to work with Binaries, trying to understand what they do and how to go about exploiting them. I also have experience in Network Security and anonymity and am currently working on a research project on Decoy Routing. Besides that I really love opensource. I have contributed to a lot of organizations including Libav, KDE, Sugarlabs, Radare2. I have participated in GSoC before and have been winner of Google Code in 2012 and 2011.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><ul><li>Github: <a href=\"https://github.com/lionaneesh\">https://github.com/lionaneesh</a></li><li>Website: <a href=\"http://anee.me\">http://anee.me</a></li><li>Mail: lionaneesh-at-gmail</li><li>Linkedin: <a href=\"http://linkedin.com/in/aneeshdogra\">linkedin.com/in/aneeshdogra</a></li></ul></p>",
            "date": "03 Jul, 2017",
            "type": "workshop",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/binary-analysis-and-exploitation-using-python~ergBa/",
            "speaker": {
                "name": "Aneesh Dogra (~lionaneesh)",
                "info": "",
                "photo": ""
            }
        },
        "159": {
            "title": "Creation of Telegram bots with Python",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>Telegram is a messaging app that focus on security and supports the use of stickers and creation of bots, as so many other useful features. To create bots there's a bot named BotFather and the Telegram Bot API. BotFather is used to create the bot and do some basic configuration. Bot features and tasks are programmed with some programming languages like Python. For Python there's a library named <a href=\"https://github.com/python-telegram-bot/python-telegram-bot\">python-telegram-bot</a> that provides an interface for the Telegram Bot API, compatible with Python versions 2.7, 3.3+ and can be used for creating chatbots, bots that create graphs for math functions, etc. </p><p>Agenda:</p><ol><li>What is a bot?</li><li>Introduction to the Telegram Bot API</li><li>First steps with BotFather</li><li>Let's write a first Telegram bot!</li><li>The bot running</li></ol><p>Requirements</p><ol><li>Python 3.3+</li><li>A text editor like Atom, Sublime Text, Notepad++</li><li>python-telegram-bot. instructions: https://github.com/python-telegram-bot/python-telegram-bot</li><li>A Telegram account created and the app for Android, Windows, Linux or Mac</li></ol></p><p>Telegram is a messaging app that focus on security and supports the use of stickers and creation of bots, as so many other useful features. To create bots there's a bot named BotFather and the Telegram Bot API. BotFather is used to create the bot and do some basic configuration. Bot features and tasks are programmed with some programming languages like Python. For Python there's a library named <a href=\"https://github.com/python-telegram-bot/python-telegram-bot\">python-telegram-bot</a> that provides an interface for the Telegram Bot API, compatible with Python versions 2.7, 3.3+ and can be used for creating chatbots, bots that create graphs for math functions, etc. </p><p>Agenda:</p><p>Requirements</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><ol><li>Basic knowledge of Python</li><li>Previous use of Telegram (Optional)</li></ol></p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>The presentation will be available in a few days here: https://github.com/mattdark/telegram-bots-presentation</p><p>I will published an article in my blog: https://medium.com/@mattdark</p><p>There are some examples on my GitHub account: https://github.com/mattdark</p></p><p>The presentation will be available in a few days here: https://github.com/mattdark/telegram-bots-presentation</p><p>I will published an article in my blog: https://medium.com/@mattdark</p><p>There are some examples on my GitHub account: https://github.com/mattdark</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>Mario Garc\u00eda has been a Free Software user and promoter for the last ten years. Volunteer for Mozilla and member of the Mozilla community in Mexico since 2011. He was member of the Firefox OS launch team for Mexico. Member of the Rust (<a href=\"http://rust-lang.org\">rust-lang.org</a>) community in Mexico. Startup Weekend Organizer during 2013. Co-founder and editor of GNU/Linux Latam, a blog about Free Software. Co-founder of Hacking Diem (<a href=\"http://hackingdiem.org\">hackingdiem.org</a>), an iniciative to promote social and tech entrepreneurship. Mentor for TechWo Community (<a href=\"http://techwo.org\">techwo.org</a>) Chapter Tuxtla Guti\u00e9rrez. He teaches Python at a local university in Tapachula, Mexico. He participated as speaker at PyCon Colombia (<a href=\"http://pycon.co\">pycon.co</a>) on February this year with a workshop about Flask (<a href=\"http://flask.pocoo.org/\">flask.pocoo.org</a>). He has attended technology and innovation events in Mexico, Colombia, Canada and Spain.</p></p><p>Mario Garc\u00eda has been a Free Software user and promoter for the last ten years. Volunteer for Mozilla and member of the Mozilla community in Mexico since 2011. He was member of the Firefox OS launch team for Mexico. Member of the Rust (<a href=\"http://rust-lang.org\">rust-lang.org</a>) community in Mexico. Startup Weekend Organizer during 2013. Co-founder and editor of GNU/Linux Latam, a blog about Free Software. Co-founder of Hacking Diem (<a href=\"http://hackingdiem.org\">hackingdiem.org</a>), an iniciative to promote social and tech entrepreneurship. Mentor for TechWo Community (<a href=\"http://techwo.org\">techwo.org</a>) Chapter Tuxtla Guti\u00e9rrez. He teaches Python at a local university in Tapachula, Mexico. He participated as speaker at PyCon Colombia (<a href=\"http://pycon.co\">pycon.co</a>) on February this year with a workshop about Flask (<a href=\"http://flask.pocoo.org/\">flask.pocoo.org</a>). He has attended technology and innovation events in Mexico, Colombia, Canada and Spain.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><ol><li>Blog: https://medium.com/@mattdark</li><li>Twitter: https://twitter.com/@mariogmd</li><li>Facebook: https://facebook.com/iscmariog</li><li>GitHub: https://github.com/mattdark</li></ol></p>",
            "date": "28 Jun, 2017",
            "type": "workshop",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/creation-of-telegram-bots-with-python~enGYa/",
            "speaker": {
                "name": "Mario Garcia (~mattdark)",
                "info": "",
                "photo": ""
            }
        },
        "160": {
            "title": "Concurrency in Python 3.0 - Writing concurrent and parallel programs in Python",
            "description": "<br><h4 class=\"heading\"><b>Description:</b></h4><p><p>This workshop is influenced and partly derived from my PyDelhi workshop <a href=\"https://cfp.pydelhi.org/pydelhi-conference-2017/proposals/concurrency-in-the-python-30-world-oh-my~aMj3b/\" title=\"Concurrency in the Python 3.0 world\">\"Concurrency in the Python 3.0 world\"</a> given this year.</p><p>From my experience, most Python developers aren't still aware of the fundamental principles of concurrent programming, parallel computing and how to identify problems that yield well to data parallelilsm. </p><p>While the PyDelhi workshop focussed on introducing different types of concurrent programming techniques available in Python, this workshop wil be focussed more on concurrency using multiple processes - via the multiprocessing library and concurrent futures modules. </p><p>The focus is to enable the attendees to pick up the skills to write programs that scale to more than 1 CPU core.</p><p>We will start off with an introduction to concurency and parallelism plus why the GIL behaves the way it does with an example.</p><ol><li>What is Concurrency - 5 min </li><li>Concurrency vs Parellelism - 5  min </li><li>The GIL weakness - Multithreading vs Multiprocessing - 10 min<ol><li>Prime number example with multiple threads &amp; multiple processes</li><li>Illustrating how GIL forces computing to 1 core</li></ol></li></ol><p>Next will be an introduction to Multiprocessing &amp; Concurrent futures with some simple examples.</p><ol><li>Quick introduction to multiprocessing - 10 min</li><li>Concurrent futures - Introduction (10 min)<ol><li>ThreadPool vs ProcessPool executors</li></ol></li></ol><p>Now time for example problems which can be scaled using data parallel technique.</p><ol><li>\"Data Parallel\" problems  - 5 min </li><li>Matrix Multiplication - 20 min<ol><li>Serial</li><li>Parallel version using Multiprocessing</li></ol></li><li>Mandelbrot Fractals - 20 min  <ol><li>Serial</li><li>Parallel version using Multiprocessing</li></ol></li><li>A simple web crawler - 20 min<ol><li>Serial</li><li>Concurrent version using Multiprocessing</li><li>Concurrent version using concurrent futures</li></ol></li></ol><p>[Break] - 5 min</p><p>Next I will demonstrate a Maze solver in Python and then show how to speed it up using parallel processing.(Note that this is experimental and maybe be replaced with something else in the actual talk !)</p><ol><li>Maze solver in Python (30 min)<ol><li>Linear</li><li>Speed up using Multiprocessing</li></ol></li></ol><p>Next the aspect of timing and measuring performance of your parallel/concurrent code.</p><p>(30 mins)</p><ol><li>Why wall clock time is not all that matters</li><li>Using simple \"time\" command</li><li>Using \"timeit\" module</li><li>Debugging concurrent code</li></ol><p>(If time allows)</p><ol><li>Generators &amp; concurrent futures - Some advanced examples - 15 min</li></ol></p><p>This workshop is influenced and partly derived from my PyDelhi workshop <a href=\"https://cfp.pydelhi.org/pydelhi-conference-2017/proposals/concurrency-in-the-python-30-world-oh-my~aMj3b/\" title=\"Concurrency in the Python 3.0 world\">\"Concurrency in the Python 3.0 world\"</a> given this year.</p><p>From my experience, most Python developers aren't still aware of the fundamental principles of concurrent programming, parallel computing and how to identify problems that yield well to data parallelilsm. </p><p>While the PyDelhi workshop focussed on introducing different types of concurrent programming techniques available in Python, this workshop wil be focussed more on concurrency using multiple processes - via the multiprocessing library and concurrent futures modules. </p><p>The focus is to enable the attendees to pick up the skills to write programs that scale to more than 1 CPU core.</p><p>We will start off with an introduction to concurency and parallelism plus why the GIL behaves the way it does with an example.</p><p>Next will be an introduction to Multiprocessing &amp; Concurrent futures with some simple examples.</p><p>Now time for example problems which can be scaled using data parallel technique.</p><p>[Break] - 5 min</p><p>Next I will demonstrate a Maze solver in Python and then show how to speed it up using parallel processing.(Note that this is experimental and maybe be replaced with something else in the actual talk !)</p><p>Next the aspect of timing and measuring performance of your parallel/concurrent code.</p><p>(30 mins)</p><p>(If time allows)</p><br><h4 class=\"heading\"><b>Prerequisites:</b></h4><p><ol><li>Python programming fundamentals - Knowledge of generators is useful indeed.</li><li>Some awareness of Python GIL.</li><li>Some awareness of concurrent computing.</li><li>The code &amp; discussions will be based on Python 3.x - the latest at that time.</li></ol><p>This workshop is <em>NOT</em> for those who are just starting out as Python programmers.</p></p><p>This workshop is <em>NOT</em> for those who are just starting out as Python programmers.</p><br><h4 class=\"heading\"><b>Content URLs:</b></h4><p><p>TBD</p><p>It will be somewhat based on the content at <a href=\"https://github.com/pythonhacker/pydelhi2017concurrency\">https://github.com/pythonhacker/pydelhi2017concurrency</a>  .Some examples such as the Mandelbrot one will be same.</p></p><p>TBD</p><p>It will be somewhat based on the content at <a href=\"https://github.com/pythonhacker/pydelhi2017concurrency\">https://github.com/pythonhacker/pydelhi2017concurrency</a>  .Some examples such as the Mandelbrot one will be same.</p><br><h4 class=\"heading\"><b>Speaker Info:</b></h4><p><p>Anand has been a long time advocate and community leader of the Python programming language in India and Bangalore.</p><p>Anand founded the BangPypers community in Feb 2005 as the result of a meeting of Bangalore Pythonistas. Discussions in this community went on to build other communities and laid the foundation of PyCon India and similar conferences.</p><p>He has 17+ years of software development experience having worked in a variety of technical roles in a number of software companies. He is currently working as Senior Architect at Yegii Inc., a startup from MIT, where he spends his time writing web crawlers to perform focussed and deep crawls for structured and unstructured data and to develop the next generation AI search engine for knowledge discovery.</p><p>His interests are high performance computing architectures, large-scale web crawling, information extraction &amp; security. </p><p>Anand is also the author of a book discussing <a href=\"http://www.blog.pythonlibrary.org/2017/06/22/book-review-software-architecture-with-python/\">Python and Software Architecture</a> for Packt Publishing, published in April 2017.</p></p><p>Anand has been a long time advocate and community leader of the Python programming language in India and Bangalore.</p><p>Anand founded the BangPypers community in Feb 2005 as the result of a meeting of Bangalore Pythonistas. Discussions in this community went on to build other communities and laid the foundation of PyCon India and similar conferences.</p><p>He has 17+ years of software development experience having worked in a variety of technical roles in a number of software companies. He is currently working as Senior Architect at Yegii Inc., a startup from MIT, where he spends his time writing web crawlers to perform focussed and deep crawls for structured and unstructured data and to develop the next generation AI search engine for knowledge discovery.</p><p>His interests are high performance computing architectures, large-scale web crawling, information extraction &amp; security. </p><p>Anand is also the author of a book discussing <a href=\"http://www.blog.pythonlibrary.org/2017/06/22/book-review-software-architecture-with-python/\">Python and Software Architecture</a> for Packt Publishing, published in April 2017.</p><br><h4 class=\"heading\"><b>Speaker Links:</b></h4><p><ol><li><a href=\"http://twitter.com/skeptichacker\">http://twitter.com/skeptichacker</a></li><li><a href=\"http://%20https://github.com/pythonhacker\">https://github.com/pythonhacker</a></li></ol></p>",
            "date": "28 Jun, 2017",
            "type": "workshop",
            "cfp": "https://in.pycon.org/cfp/2017/proposals/concurrency-in-python-30-writing-concurrent-and-parallel-programs-in-python~bm7Ee/",
            "speaker": {
                "name": "Anand B Pillai (~anand5)",
                "info": "",
                "photo": ""
            }
        }
    }]
}