Шай ШварцUnderstanding Machine Learning:
From Theory to Algorithms
c
2014 by Shai Shalev-Shwartz and Shai Ben-David
Published 2014 by Cambridge University Press.
This copy is for personal use only. Not for distribution.
Do not post. Please link to:
http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning
Please note: This copy is almost, but not entirely, identical to the printed version of the book. In particular, page numbers are not identical (but section numbers are the same).
Understanding Machine Learning
Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics of the field, the book covers a wide array of central topics that have not been addressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for an advanced undergraduate or beginning graduate course, the text makes the fundamentals and algorithms of machine learning accessible to students and nonexpert readers in statistics, computer science, mathematics, and engineering.
Shai Shalev-Shwartz is an Associate Professor at the School of Computer Science and Engineering at The Hebrew University, Israel.
Shai Ben-David is a Professor in the School of Computer Science at the University of Waterloo, Canada.
UNDERSTANDING
MACHINE LEARNING
From Theory to
Algorithms
Shai Shalev-Shwartz
The Hebrew University, Jerusalem
Shai Ben-David
University of Waterloo, Canada
32 Avenue of the Americas, New York, NY 10013-2473, USA Cambridge University Press is part of the University of Cambridge.