TY  - BOOK
AU  - Shai Shalev-Shwartz
AU  - Shai Ben-David
TI  - Understanding Machine Learning: From Theory to Algorithms
SN  - 978-1139948517
U1  - 006.31 SHW 
PY  - 2025///
CY  - Cambridge University Press
PB  - New Delhi
KW  - CSE
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
ER  -