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
The Elements of Statistical Learning: Data Mining, Inference, and Predictionby T. Hastie, R. Tibshirani, J. Friedman - Springer
This book brings together many of the important new ideas in learning, and explains them in a statistical framework. The authors emphasize the methods and their conceptual underpinnings rather than their theoretical properties.
(40090 views)
Machine Learning and Data Mining: Lecture Notesby Aaron Hertzmann - University of Toronto
Contents: Introduction to Machine Learning; Linear Regression; Nonlinear Regression; Quadratics; Basic Probability Theory; Probability Density Functions; Estimation; Classification; Gradient Descent; Cross Validation; Bayesian Methods; and more.
(10005 views)
Reinforcement Learning: An Introductionby Richard S. Sutton, Andrew G. Barto - The MIT Press
The book provides a clear and simple account of the key ideas and algorithms of reinforcement learning. It covers the history and the most recent developments and applications. The only necessary mathematical background are concepts of probability.
(26898 views)
Machine Learningby 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.
(16231 views)