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.
- Chapter 1: Using neural nets to recognize handwritten digits - in progress
- 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
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