|Foundations of Machine Learning 2nd Ed (MIT Press)|
|Wednesday, 23 January 2019|
This book is a general introduction to machine learning that covers fundamental modern topics while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. Authors Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar, and Francis Bachaim focuses on the analysis and theory of algorithms and present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics.
Author: Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar, and Francis Bach
Topics covered include:
This second edition has three new chapters, on model selection, maximum entropy models, and conditional entropy models.
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