Machine Learning Resources

A*
	http://www.redblobgames.com/pathfinding/a-star/introduction.html
	http://web.mit.edu/eranki/www/tutorials/search/
	https://www.raywenderlich.com/4946/introduction-to-a-pathfinding
Neural network
	http://www.nltk.org/book/ch06.html
	https://spin.atomicobject.com/2014/06/24/gradient-descent-linear-regression/
	https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/
	https://www.quora.com/What-are-the-good-sources-to-understand-the-mathematical-understanding-of-the-Backpropagation-algorithm
	http://iamtrask.github.io/2015/07/12/basic-python-network/
	http://iamtrask.github.io/2017/03/21/synthetic-gradients/
	http://outlace.com/Gradient-Descent.html
	http://outlace.com/miniga.html
	http://outlace.com/archives/%7Bslug%7D/
Competitive learning:
	https://web.stanford.edu/group/pdplab/pdphandbook/handbookch7.html#x18-900006.1
Hopfield network:
	https://www.youtube.com/watch?v=HoWJzeAT9uc
	https://www.youtube.com/watch?v=4JoblKhVnu0
	http://www.comp.leeds.ac.uk/ai23/reading/Hopfield.pdf
	http://fuzzy.cs.ovgu.de/ci/nn/v07_hopfield_en.pdf
	http://authors.library.caltech.edu/6596/1/FONpra89.pdf
	http://web.cs.ucla.edu/~rosen/161/notes/hopfield.html
OCR:
	http://perun.pmf.uns.ac.rs/radovanovic/dmsem/completed/2006/OCR.pdf
Fuzzy Logic:
	http://www.springer.com/cda/content/document/cda_downloaddocument/9781846284687-c1.pdf
	http://www.controleng.com/single-article/artificial-intelligence-fuzzy-logic-explained/8f3478c13384a2771ddb7e93a2b6243d.html
	http://petro.tanrei.ca/fuzzylogic/fuzzy_negnevistky.html
Genetic Algorithm:
	https://www.youtube.com/playlist?list=PLRqwX-V7Uu6bJM3VgzjNV5YxVxUwzALHV
Reinforcement Learning:
	Off-Policy:
		http://mnemstudio.org/path-finding-q-learning-tutorial.htm
		https://www.youtube.com/watch?v=DgRqxKt2DYE
	On-Policy:
		http://webdocs.cs.ualberta.ca/~sutton/book/ebook/node64.html
Other:
	http://natureofcode.com/book/chapter-10-neural-networks/
	http://www.holehouse.org/mlclass/08_Neural_Networks_Representation.html