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May 20th, 2018
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  1. no idea for Matlab, I was forced to learn it in some undergrad course and never touched it again in favor of python+numpy
  2.  
  3. so there is my resource list for python:
  4. - Dive Into Python 3 http://www.diveintopython3.net/
  5. - Automate the Boring Stuff with Python book https://automatetheboringstuff.com/
  6. - Formatted printing overview https://pyformat.info/
  7. - Python's Magic Methods https://rszalski.github.io/magicmethods/
  8. - Google's Python Style Guide https://google.github.io/styleguide/pyguide.html and ofc PEP8 style guide
  9. - Key differences between Python 2.x and 3.x (nowadays you can ignore 2.x existence) http://sebastianraschka.com/Articles/2014_python_2_3_key_diff.html
  10. - Python Numpy Tutorial from Stanford's CS231n course https://cs231n.github.io/python-numpy-tutorial/
  11. - Python Data Science Handbook (slightly outdated, the IPython notebook is now Jupyter Notebook) https://jakevdp.github.io/PythonDataScienceHandbook/
  12. - Introduction to statistics using Numpy https://mubaris.com/2017/09/09/introduction-to-statistics-using-numpy/
  13. - Advanced Numpy Techniques http://nbviewer.jupyter.org/github/vlad17/np-learn/blob/master/presentation.ipynb
  14. - Numpy Exercises for Data Analysis https://www.machinelearningplus.com/python/101-numpy-exercises-python/
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