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Math for Deep Learning
book

Math for Deep Learning

by Ronald T. Kneusel
October 2021
Intermediate to advanced
344 pages
8h 51m
English
No Starch Press
Content preview from Math for Deep Learning

9DATA FLOW IN NEURAL NETWORKS

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In this chapter, I’ll present how data flows through a trained neural network. In other words, we’ll look at how to go from an input vector or tensor to the output, and the form the data takes along the way. If you’re already familiar with how neural networks function, great, but if not, walking through how data flows from layer to layer will help you build an understanding of the processes involved.

First, we’ll look at how we represent data in two different kinds of networks. Then, we’ll work through a traditional feedforward network to give ourselves a solid foundation. We’ll see just how compact inference with ...

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Publisher Resources

ISBN: 9781098129101