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Deep Learning and the Game of Go
book

Deep Learning and the Game of Go

by Kevin Ferguson, Max Pumperla
January 2019
Intermediate to advanced content levelIntermediate to advanced
384 pages
13h 27m
English
Manning Publications
Content preview from Deep Learning and the Game of Go

Appendix B. The backpropagation algorithm

Chapter 5 introduced sequential neural networks and feed-forward networks in particular. We briefly talked about the backpropagation algorithm, which is used to train neural networks. This appendix explains in a bit more detail how to arrive at the gradients and parameter updates that we simply stated and used in chapter 5.

We’ll first derive the backpropagation algorithm for feed-forward neural networks and then discuss how to extend the algorithm to more-general sequential and nonsequential networks. Before going deeper into the math, let’s define our setup and introduce notation that will help along the way.

A bit of notation

In this section, you’ll work with a feed-forward neural network with ...

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