Further Details

Title: Understanding Machine Learning
Condition: New
Description: 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 a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics unaddressed 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 advanced undergraduates or beginning graduates, the text makes the fundamentals and algorithms of machine learning accessible to students and non-expert readers in statistics, computer science, mathematics and engineering.
Author: Shai Shalev-Shwartz, Shai Ben-David
Format: Hardback
EAN: 9781107057135
ISBN: 9781107057135
Genre: Computing & Internet
Country/Region of Manufacture: GB
Item Height: 260mm
Item Length: 183mm
Item Weight: 910g
Subtitle: From Theory to Algorithms
Publisher: Cambridge University Press
Release Date: 05/19/2014
Language: English
Item Width: 28mm
Release Year: 2014

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