**Bayesian Reasoning and Machine Learning**

by David Barber

**Publisher**: Cambridge University Press 2011**ISBN/ASIN**: 0521518148**ISBN-13**: 9780521518147**Number of pages**: 644

**Description**:

The book is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models.

Download or read it online for free here:

**Download link**

(15MB, PDF)

## Similar books

**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.

(

**1357**views)

**Introduction to Machine Learning**

by

**Alex Smola, S.V.N. Vishwanathan**-

**Cambridge University Press**

Over the past two decades Machine Learning has become one of the mainstays of information technology and a rather central part of our life. Smart data analysis will become even more pervasive as a necessary ingredient for technological progress.

(

**3143**views)

**Modeling Agents with Probabilistic Programs**

by

**Owain Evans, et al.**-

**AgentModels.org**

This book describes and implements models of rational agents for (PO)MDPs and Reinforcement Learning. One motivation is to create richer models of human planning, which capture human biases. The book assumes basic programming experience.

(

**1209**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).

(

**15364**views)