Anatomy of Deep Learning Principles
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Anatomy of Deep Learning Principles

Writing a Deep Learning Library from Scratch

About the Book

This book introduces the basic principles and implementation process of deep learning in a simple way, and uses python's numpy library to build its own deep learning library from scratch instead of using existing deep learning libraries. On the basis of introducing basic knowledge of Python programming, calculus, and probability statistics, the core basic knowledge of deep learning such as regression model, neural network, convolutional neural network, recurrent neural network, and generative network is introduced in sequence according to the development of deep learning. While analyzing the principle in a simple way, it provides a detailed code implementation process. It is like not teaching you how to use weapons and mobile phones, but teaching you how to make weapons and mobile phones by yourself. This book is not a tutorial on the use of existing deep learning libraries, but an analysis of how to develop deep learning libraries from 0. This method of combining the principle from 0 with code implementation can enable readers to better understand the basic principles of deep learning and the design ideas of popular deep learning libraries.

This book is a translation into English of 解剖深度学习原理 which was originally written in Chinese (Simplified).

About the Author


C9本科,高考数学物理1小时交卷、超出清华分数线20多分. Texas A&M、休斯顿大学访问学者. 曾从事计算机图形学、视觉等科研,目前主要从事计算机编程等网络课程的工作,写了3本书:C++17从入门到精通、Python3从入门到实战、解剖深度学习原理-从0实现深度学习库。在YouTube频道hwdong上发布免费计算机相关的教学课程。

Table of Contents

Anotomy of deep learning priciples and how to implement a deep learning libray from scratch

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