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This is specifically called out by the authors. Linear algebra is less likely to be covered in computer science courses than other types of math, such as discrete mathematics. Therefore, we can use the topics covered in the chapter on linear algebra as a guide to the topics you may be expected to be familiar with as a deep learning and machine learning practitioner. This part of the book introduces the basic mathematical concepts needed to understand deep learning. Given the expertise of the authors of the book, it is fair to say that the chapter on linear algebra provides a well reasoned set of prerequisites for deep learning, and perhaps more generally much of machine learning. This part of the book includes four chapters they are: In the book, the authors provide a part titled “ Applied Math and Machine Learning Basics” intended to provide the background in applied mathematics and machine learning required to understand the deep learning material presented in the rest of the book. The book “ Deep Learning” by Ian Goodfellow, Yoshua Bengio, and Aaron Courville is the de facto textbook for deep learning. Photo by Quinn Dombrowski, some rights reserved. Kick-start your project with my new book Linear Algebra for Machine Learning, including step-by-step tutorials and the Python source code files for all examples. Suggestions for how to get the most out of the chapter as a crash course in linear algebra.The progression through these topics and their culmination.The topics suggested as prerequisites for deep learning by experts in the field.

In this post, you will discover the crash course in linear algebra for deep learning presented in the de facto textbook on deep learning. In their seminal textbook on deep learning, Ian Goodfellow and others present chapters covering the prerequisite mathematical concepts for deep learning, including a chapter on linear algebra. Although important, this area of mathematics is seldom covered by computer science or software engineering degree programs. Generally, an understanding of linear algebra (or parts thereof) is presented as a prerequisite for machine learning. Linear algebra is a field of applied mathematics that is a prerequisite to reading and understanding the formal description of deep learning methods, such as in papers and textbooks.