Deep Learning from Scratch: Building with Python from First Principles
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With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You’ll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way.
Author Seth Weidman shows you how neural networks work using a first principles approach. You’ll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you’ll be set up for success on all future deep learning projects.
This book provides:
- Extremely clear and thorough mental models—accompanied by working code examples and mathematical explanations—for understanding neural networks
- Methods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented framework
- Working implementations and clear-cut explanations of convolutional and recurrent neural networks
- Implementation of these neural network concepts using the popular PyTorch framework
Table of Contents
Review of Deep Learning from Scratch: Building with Python from First Principles
Just started reading this online. Fantastic explanations relating the math and diagrams. The author has done an amazing job, and his hard work has helped immensely. Just what I needed at this point.
That said, it appears the printed book’s (excellent) illustrations and code are devoid of color. This happens with other O’Reilly books, and I’m not clear why the author’s work was not respected.
Compare the online version (if you have the very expensive subscription) with the printed one, and you’ll see what I mean.
With apologies to the author, I DO NOT recommend that you purchase the printed book. You won’t get what you paid for. Perhaps this feedback will make it’s way to O’Reilly and help in some way.
About the Author
Seth Weidman is a data scientist who has applied and taught machine learning concepts for several years. He started out as the first data scientist at Trunk Club, where he built lead scoring models and recommender systems, and currently works at Facebook, where he builds machine learning models for their infrastructure team. In between he taught data science and machine learning for the bootcamps and on the corporate training team at Metis. He is passionate about explaining complex concepts simply, striving to find the simplicity on the other side of complexity.