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Fundamentals of Probability and Statistics for Machine Learning

by Ethem Alpaydın

ISBN: 9780262049818

Publisher: The MIT Press

Pub Date: December 2, 2025

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

Probability and Statistics for Economics and Business

An Introduction Using R

by Jason Abrevaya

ISBN: 9780262553360

Publisher: The MIT Press

Pub Date: November 25, 2025

A modern introduction to probability and statistics for economics and business undergraduates, using the R programming language.

Mathematics in Biology

by Markus Meister, Kyu Hyun Lee and Ruben Portugues

ISBN: 9780262049405

Publisher: The MIT Press

Pub Date: February 18, 2025

A concise but rigorous textbook for advanced undergraduate and graduate students across the biological sciences that provides a foundation for understanding the methods used in quantitative biology.

The Math You Need

A Comprehensive Survey of Undergraduate Mathematics

by Thomas Mack

ISBN: 9780262546324

Publisher: The MIT Press

Pub Date: October 31, 2023

A comprehensive survey of undergraduate mathematics, compressing four years of study into one robust overview.

Causal Analysis

Impact Evaluation and Causal Machine Learning with Applications in R

by Martin Huber

ISBN: 9780262545914

Publisher: The MIT Press

Pub Date: August 1, 2023

A comprehensive and cutting-edge introduction to quantitative methods of causal analysis, including new trends in machine learning.

Distributional Reinforcement Learning

by Marc G. Bellemare, Will Dabney and Mark Rowland

ISBN: 9780262048019

Publisher: The MIT Press

Pub Date: May 30, 2023

The first comprehensive guide to distributional reinforcement learning, providing a new mathematical formalism for thinking about decisions from a probabilistic perspective.