Logo

Machine Learning: A Probabilistic Perspective

Large book cover: Machine Learning: A Probabilistic Perspective

Machine Learning: A Probabilistic Perspective
by

Publisher: The MIT Press
ISBN-13: 9780262018029
Number of pages: 1098

Description:
A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms.

Home page url

Download or read it online for free here:
Download link
(46MB, PDF)

Similar books

Book cover: Machine Learning, Neural and Statistical ClassificationMachine Learning, Neural and Statistical Classification
by - Ellis Horwood
The book provides a review of different approaches to classification, compares their performance on challenging data-sets, and draws conclusions on their applicability to realistic industrial problems. A wide variety of approaches has been taken.
(27919 views)
Book cover: A Survey of Statistical Network ModelsA Survey of Statistical Network Models
by - arXiv
We begin with the historical development of statistical network modeling and then we introduce some examples in the network literature. Our subsequent discussion focuses on prominent static and dynamic network models and their interconnections.
(8394 views)
Book cover: Bayesian Reasoning and Machine LearningBayesian Reasoning and Machine Learning
by - Cambridge University Press
The book is designed for final-year undergraduate students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basics to advanced techniques within the framework of graphical models.
(22458 views)
Book cover: An Introduction to Statistical LearningAn Introduction to Statistical Learning
by - Springer
This book provides an introduction to statistical learning methods. It contains a number of R labs with detailed explanations on how to implement the various methods in real life settings and it is a valuable resource for a practicing data scientist.
(9856 views)