This comprehensive text covers the key mathematical concepts that underpin modern machine learning, with a focus on linear algebra, calculus, and probability theory.

Apr 23, 2020 · '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 …

This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites.

May 30, 2025 · With this book, you’ll explore the core disciplines of linear algebra, calculus, and probability theory essential for mastering advanced machine learning concepts.

This textbook is meant to summarize the mathematical underpinnings of important machine learning applications and to connect the mathematical topics to their use in machine learning problems.

Jun 15, 2021 · Deisenroth, Marc Peter, A. Aldo Faisal and Cheng Soon Ong. Mathematics for Machine Learning. Cambridge University Press, 2020. Want to Read saving… Error rating book. Refresh and …

The first part of this book introduces the mathematical concepts and foundations needed to talk about the three main components of a machine learning system: data, models, and learning.

The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now …

'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 …