Fundamentals of Probability and Statistics for Machine Learning

Ethem Alpaydin

$200

Hardback

Forthcoming
Pre-Order now

QTY:

English

MIT Press
16 December 2025

Computing: general

An introductory textbook for undergraduate or beginning graduate students that integrates probability and statistics with their applications in machine learning.

An introductory textbook for undergraduate or beginning graduate students that integrates probability and statistics with their applications in machine learning.

Most curricula have students take an undergraduate course on probability and statistics before turning to machine learning. In this innovative textbook, Ethem Alpaydın offers an alternative tack by integrating these subjects for a first course on learning from data. Alpaydın accessibly connects machine learning to its roots in probability and statistics, starting with the basics of random experiments and probabilities and eventually moving to complex topics such as artificial neural networks. With a practical emphasis and learn-by-doing approach, this unique text offers comprehensive coverage of the elements fundamental to an empirical understanding of machine learning in a data science context.

Consolidates foundational knowledge and key techniques needed for modern data science Emphasizes hands-on learning Covers mathematical fundamentals of probability and statistics and ML basics Suits undergraduates as well as self-learners with basic programming experience Includes slides, solutions, and code

By: Ethem Alpaydin
Imprint: MIT Press
Country of Publication: United States
Dimensions: Height: 229mm, Width: 178mm,
Weight: 567g
ISBN: 9780262049818
ISBN 10: 0262049813
Pages: 544
Publication Date: 16 December 2025
Audience: General/trade , ELT Advanced
Format: Hardback
Publisher's Status: Forthcoming

Ethem Alpaydın is Professor in the Department of Computer Engineering at zyegin University and a member of the Science Academy, Istanbul. He is the author of the widely used textbook, Introduction to Machine Learning, now in its fourth edition, and Machine Learning, both published by the MIT Press.