TY  - BOOK
AU  - Shalev-Shwartz,Shai
AU  - Ben-David,Shai
TI  - Understanding Machine Learning: From Theory to Algorithms 
SN  - 9781107298019
AV  - ebookQ325.5 .S475 2014
PY  - 2014///
CY  - Cambridge
PB  - Cambridge University Press
KW  - Machine learning
KW  - Algorithms
N1  - Title from publisher's bibliographic system (viewed on 08 Oct 2015)
N2  - 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
UR  - https://eresourcesptsl.ukm.remotexs.co/user/login?url=http://dx.doi.org/10.1017/CBO9781107298019
ER  -