How long does it take to read Mathematics for Machine Learning?
Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
Mathematics for Machine Learning by Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong takes about 7 hours 18 minutes to read at 250 words a minute.
About 7 hours 18 minutes
A weekend read
First published 2019. 398 pages, about 109,450 words.
15 days at 30 minutes a day
Estimate based on 275 words per page.
At other speeds
| Slow, 150 words a minute | 12 hours 10 minutes |
| Average, 250 words a minute | 7 hours 18 minutes |
| Fast, 400 words a minute | 4 hours 34 minutes |
The page count is the median across 4 editions, so your copy may differ. How we calculate.
About the book
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.
Subjects: machine learning, mathematics, linear algebra, analytic geometry, matrix decompositions, vector calculus
