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Translation of Neural Networks and Deep Learning by Michael Nielsen
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README.md
chapter1.rst

README.md

Neural networks and Deep learning ko

This is a translation of Neural Networks and Deep Learning by Michael Nielsen. I started this project to learn more about deep learning. Also I wanted to share good study material to Korean students who also have a same interest.

Status

  • Chapter 1: Using neural nets to recognize handwritten digits - in progress
  • Perceptrons
  • Sigmoid neurons
  • The architecture of neural networks
  • A simple network to classify handwritten digits
  • Learning with gradient descent
  • Implementing our network to classify digits
  • Toward deep learning
  • Chapter 2: How the backpropagation algorithm works
  • Warm up: a fast matrix-based approach to computing the output from a neural network
  • The two assumptions we need about the cost function
  • The Hadamard product
  • The four fundamental equations behind backpropagation
  • Proof of the four fundamental equations (optional)
  • The backpropagation algorithm
  • The code for backpropagation
  • In what sense is backpropagation a fast algorithm?
  • Backpropagation: the big picture

Translator

Copyright

This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License. This means you're free to copy, share, and build on this book, but not to sell it.

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