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Grokking deep learning
Trask A., Manning Publications Co., Shelter Island, NY, 2019. 336 pp. Type: Book (978-1-617293-70-2)
Date Reviewed: Feb 14 2020

Deep learning is a hot topic in artificial intelligence (AI). It is exciting to see a book that can help readers understand the ideas of deep learning without advanced knowledge of mathematics.

The book is divided into 16 chapters. Chapter 1 presents the basic ideas of getting started with deep learning. Chapter 2 introduces fundamental concepts in the field. Chapter 3 talks about forward propagation and includes an example of a simple network making a prediction. Chapters 4 and 5 present gradient descent to minimize error. Chapter 6 introduces backpropagation. Chapter 7 focuses on how to picture neural networks in your head.

Chapter 8 introduces regularization and batching. Chapter 9 is dedicated to activation functions. Chapter 10 discusses convolutional neural networks. Chapter 11 starts to introduce natural language processing. In chapter 12, the author presents recurrent neural networks. Chapter 13 teaches readers how to build a deep learning framework from scratch. Chapter 14 uses a recurrent neural network to tackle language modeling. Chapter 15 focuses on privacy in data. Chapter 16, the last chapter, provides tools and resources to readers who want to continue on their deep learning journey.

The book presents the logic and contents very clearly. It covers every basic aspect of deep learning. The examples come with source code written in Python, provided on the book’s website (https://www.manning.com/books/grokking-deep-learning), so readers can easily try the examples. It is a great book for deep learning beginners, who should go through it chapter by chapter.

The author states: “I’ve intentionally written this book with what I believe is the lowest barrier to entry possible. No knowledge of linear algebra, calculus, convex optimization, or even machine learning is assumed.” This book can serve as the first book for people who want to enter the deep learning field.

Reviewer:  Zhaoqiang Lai Review #: CR146891 (2006-0117)
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