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This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This final volume, Learning, builds on the foundational topics established in volume I to provide a thorough introduction to learning methods, addressing techniques such as least-squares methods, regularization, online learning, kernel methods, feedforward and recurrent neural networks, meta-learning, and adversarial…
This is the third volume of a three volume textbook. We encourage instructors to refer to the Course Guide in the Resources area for more information on how the volumes can be combined or used individually to support different courses.
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Foundations, Volume 1
Online publication date: 17 February 2023
Hardback publication date: 22 December 2022
Inference, Volume 2
Online publication date: 17 March 2023
Hardback publication date: 22 December 2022
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Online publication date: 23 September 2020