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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

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Product type Paperback
Published in Mar 2021
Publisher Packt
ISBN-13 9781800206137
Length 316 pages
Edition 1st Edition
Languages
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Authors (2):
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Shigeo Yushita Shigeo Yushita
Author Profile Icon Shigeo Yushita
Shigeo Yushita
Koki Saitoh Koki Saitoh
Author Profile Icon Koki Saitoh
Koki Saitoh
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Toc

Table of Contents (11) Chapters Close

Preface 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

Concept of this book

This book is about deep learning and covers the knowledge required to understand it step by step from the basics, including what it is, what it entails, and how it works as simply as possible to give readers a deeper understanding of the relevant technologies.

Then what should we do to better understand deep learning? Well, one of the best ways is by making something—for example, performing practical tasks to create a program that runs from scratch that promotes critical thinking while reading a source code. Now, "from scratch" in this context means using as little external already-made items (such as libraries and tools) as possible. The goal of this book is to use as little as possible of these "black boxes", whose contents are unknown, meaning that you begin with minimal basic knowledge, upon which you will build, analyze, and implement to understand and make state-of-the-art deep learning programs. If you were to compare this...

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