Can I read Mathematics for Machine Learning on EtoBox?

Mathematics for Machine Learning by Marc Peter Deisenroth; A Aldo Faisal; Cheng Soon Ong; Cambridge University Press is a science book available to read on EtoBox.

What is Mathematics for Machine Learning about?

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability, and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models, and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.

Who reads Mathematics for Machine Learning?

Author

Marc Peter Deisenroth; A Aldo Faisal; Cheng Soon Ong; Cambridge University Press

Publisher

Cambridge University Press (Virtual Publishing)

Published

2020

Language

EN

ISBN

9781108470049

Category

science

Subjects

Computer Science, Stem

Rating

4.6 / 5 (677 ratings)

Updated

2026-03-14