Skip to Content
Hands-On Mathematics for Deep Learning
book

Hands-On Mathematics for Deep Learning

by Jay Dawani
June 2020
Intermediate to advanced
364 pages
13h 56m
English
Packt Publishing
Content preview from Hands-On Mathematics for Deep Learning

Linear Algebra

In this chapter, we will be covering the main concepts of linear algebra, and the concepts learned here will serve as the backbone on which we will learn all the concepts in the chapters to come, so it is important that you pay attention.

It is very important for you to know that these chapters cannot be substituted for an education in mathematics; they exist merely to help you better grasp the concepts of deep learning and how various architectures work and to develop an intuition for why that is, so you can become a better practitioner in the field.

At its core, algebra is nothing more than the study of mathematical symbols and the rules for manipulating these symbols. The field of algebra acts as a unifier for all of mathematics ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Math for Deep Learning

Math for Deep Learning

Ronald T. Kneusel
Deep Learning with PyTorch

Deep Learning with PyTorch

Eli Stevens, Thomas Viehmann, Luca Pietro Giovanni Antiga

Publisher Resources

ISBN: 9781838647292