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Deep Learning from the Basics

You're reading from Deep Learning from the Basics Python and Deep Learning: Theory and Implementation

Product type Paperback

Published in Mar 2021

Publisher Packt

ISBN-13 9781800206137

Length 316 pages

Edition 1st Edition

Languages

Python

Concepts

Deep Learning

Authors (2):

Shigeo Yushita

Koki Saitoh

View More author details

Table of Contents (11) Chapters

Preface

About the Book

Introduction

1. Introduction to Python FREE CHAPTER

2. Perceptrons

3. Neural Networks

4. Neural Network Training

5. Backpropagation

6. Training Techniques

7. Convolutional Neural Networks

8. Deep Learning

Appendix A

5. Backpropagation

The previous chapter described neural network training. There, the gradient of a weight parameter in the neural network (i.e., the gradient of the loss function for a weight parameter) was obtained by using numerical differentiation. Numerical differentiation is simple, and its implementation is easy, but it has the disadvantage that calculation takes time. This chapter covers backpropagation, which is a more efficient way to calculate the gradients of weight parameters.

There are two ways to understand backpropagation correctly. One of them uses "equations," while the other uses computational graphs. The former is a common way, and many books about machine learning expand on this by focusing on formulas. This is good because it is strict and simple, but it may hide essential details or end in a meaningless list of equations.

Therefore, this chapter will use computational graphs so that you can understand backpropagation "visually.&quot...

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Authors (2)

Shigeo Yushita

Shigeo Yushita

Contracted

See other products by Shigeo Yushita

Saitoh

Saitoh

Koki Saitoh was born in Tsushima, Nagasaki in 1984. He graduated from the engineering department of the Tokyo Institute of Technology and completed a master's course at the Graduate School of Interdisciplinary Information Studies at the University of Tokyo. Currently, he conducts research and development in computer vision and machine learning. He has authored Python 3 in Practice, The Elements of Computing Systems, and Building Machine Learning Systems with Python, translations of which are published by O'Reilly, Japan.

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