PUP acquires Patterns, Predictions, and Actions

Editor for Neuroscience and Computer Science Hallie Stebbins has acquired Patterns, Predictions, and Actions a graduate-level introductory machine learning textbook by Moritz Hardt and Benjamin Recht.

Patterns, Predictions, and Actions offers students a broad perspective, deeply informed by theory, on the field of machine learning. The authors argue that the pattern classification research of the 1960s remains relevant for recent advances in machine learning. The book’s early chapters extend the fundamentals of pattern classification with recent developments in optimization and generalization. Later chapters depart from the traditional way in which machine learning is usually taught, covering datasets, causality, and sequential and dynamic models. Throughout the text, the authors highlight the significant potential harms, limitations, and social consequences of machine learning, which the authors assert need to be addressed in the context of modern machine learning instruction.

Patterns, Predictions, and Actions will be an integral contribution an expanding textbook publishing program at Princeton University Press. Alongside an actively evolving acquisitions strategy, this initiative is bolstered by the development of several new roles—a Senior Textbook Editor, Textbook Coordinator, and Chief Textbook Sales and Marketing Strategist—designed to support active author-editor collaborations and highly innovative marketing interventions.

About the Authors

Moritz Hardt is an Assistant Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley and co-founder of the Workshop on Fairness, Accountability, and Transparency in Machine Learning. Professor Hardt investigates the consequential interplay of algorithms, data, and society. He is the recipient of a National Science Foundation CAREER Award and an Alfred P. Sloan Research Fellowship, among other honors.

Benjamin Recht 
is an Associate Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He is the recipient of a Presidential Early Career Award for Scientists and Engineers, an Alfred P. Sloan Research Fellowship, the SIAM/MOS Lagrange Prize in Continuous Optimization, the Jamon Prize, the William O. Baker Award for Initiatives in Research, and has twice received the NeurIPS Test of Time Award.