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A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines.Gaussian …
An argument that-despite dramatic advances in the field-artificial intelligence is nowhere near developing systems that are genuinely intelligent.In this provocative book, Brian …
A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems.This book offers a comprehensive introduction to …
An argument in favor of finding a place for humans (and humanness) in the future digital economy.In the digital economy, accountants, baristas, and cashiers can be automated out of …
An overview of recent efforts in the machine learning community to deal with dataset and covariate shift, which occurs when test and training inputs and outputs have different …
Students explore the idea that thinking is a form of computation by learning to write simple computer programs for tasks that require thought. This book guides students through an …
A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with …
A project-based guide to the basics of deep learning.This concise, project-driven guide to deep learning takes readers through a series of program-writing tasks that introduce them …
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms.This book is a general introduction to machine learning that can …
An examination of the implications for society of rapidly advancing artificial intelligence systems, combining a humanities perspective with technical analysis; includes exercises …