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By Adam Wulf on November 9, 2017
Over the past year I’ve been reading and learning about neural networks, how they work, and how to use them. I’ve found the overwhelming majority of tutorials and introductions to NN either: a) focus on the math and derivations, or b) focus on the code and tools, but rarely seem to c) match the math 1:1 with the code. Both of these tutorial styles are often guilty of handwaving and simplifying the derivations, making it difficult for me to follow exactly how the math and code relate to each other.