Mathematics for Machine Learning 1st Edition
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From the Publisher
‘The field of machine learning has grown dramatically in recent years, with an increasingly impressive spectrum of successful applications. This comprehensive text covers the key mathematical concepts that underpin modern machine learning, with a focus on linear algebra, calculus, and probability theory. It will prove valuable both as a tutorial for newcomers to the field, and as a reference text for machine learning researchers and engineers.' Christopher Bishop, Microsoft Research Cambridge
'This book provides a beautiful exposition of the mathematics underpinning modern machine learning. Highly recommended for anyone wanting a one-stop-shop to acquire a deep understanding of machine learning foundations.' Pieter Abbeel, University of California, Berkeley
- Publisher : Cambridge University Press; 1st edition (April 1, 1920)
- Language : English
- Paperback : 398 pages
- ISBN-10 : 110845514X
- ISBN-13 : 978-1108455145
- Item Weight : 1.76 pounds
- Dimensions : 7 x 0.7 x 9.9 inches
- Best Sellers Rank: #18,579 in Books (See Top 100 in Books)
- Customer Reviews:
Top reviews from the United States
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The explanations are clear, and the book is designed to bring clarity and lucidity onto the topics, not send the student on an endless pit of proofs and rigor.
Highly recommended. Best book I have came across so far for starting my own ML journey.
It is not intended to be, but is a masterpiece that brings out the beauty of mathematics.
You have to be aware this paperback version doesn't come with solutions. One of my reason to buy this is for the solutions. It turned out that only instructors can request solutions from the press company.
Top reviews from other countries
Moreover, I absolutely love the 4cm margins at the outer edges of pages, as I like pencilling my notes in blank spaces or place sticky notes there. Helpful footnotes in the margins.
Gracias Amazon !
Noviembre 23, 2020