Basics of Linear Algebra for Machine Learning
Author | : Jason Brownlee |
Publisher | : Machine Learning Mastery |
Total Pages | : 211 |
Release | : 2018-01-24 |
ISBN-13 | : |
ISBN-10 | : |
Rating | : 4/5 ( Downloads) |
Download or read book Basics of Linear Algebra for Machine Learning written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2018-01-24 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear algebra is a pillar of machine learning. You cannot develop a deep understanding and application of machine learning without it. In this laser-focused Ebook, you will finally cut through the equations, Greek letters, and confusion, and discover the topics in linear algebra that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover what linear algebra is, the importance of linear algebra to machine learning, vector, and matrix operations, matrix factorization, principal component analysis, and much more.