**Understanding Machine Learning: From Theory to Algorithms**

by Shai Shalev-Shwartz, Shai Ben-David

**Publisher**: Cambridge University Press 2014**ISBN/ASIN**: 1107057132**ISBN-13**: 9781107057135**Number of pages**: 449

**Description**:

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.

Download or read it online for free here:

**Download link**

(2.5MB, PDF)

## Similar books

**Boosting: Foundations and Algorithms**

by

**Robert E. Schapire, Yoav Freund**-

**The MIT Press**

Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate 'rules of thumb'. A remarkably rich theory has evolved around boosting, with connections to a range of topics.

(

**1302**views)

**Introduction to Machine Learning**

by

**Amnon Shashua**-

**arXiv**

Introduction to Machine learning covering Statistical Inference (Bayes, EM, ML/MaxEnt duality), algebraic and spectral methods (PCA, LDA, CCA, Clustering), and PAC learning (the Formal model, VC dimension, Double Sampling theorem).

(

**15380**views)

**Machine Learning**

by

**Abdelhamid Mellouk, Abdennacer Chebira**-

**InTech**

Neural machine learning approaches, Hamiltonian neural networks, similarity discriminant analysis, machine learning methods for spoken dialogue simulation and optimization, linear subspace learning for facial expression analysis, and more.

(

**9994**views)

**Machine Learning for Designers**

by

**Patrick Hebron**-

**O'Reilly Media**

This book introduces you to contemporary machine learning systems and helps you integrate machine-learning capabilities into your user-facing designs. Patrick Hebron explains how machine-learning applications can affect the way you design websites.

(

**1365**views)