Graphical Models for Machine Learning and Digital Communication, PDF eBook

Graphical Models for Machine Learning and Digital Communication PDF

Part of the Adaptive Computation and Machine Learning Series series

PDF

Download Now
  • Information

Description

A variety of problems in machine learning and digital communication deal with complex but structured natural or artificial systems. In this book, Brendan Frey uses graphical models as an overarching framework to describe and solve problems of pattern classification, unsupervised learning, data compression, and channel coding. Using probabilistic structures such as Bayesian belief networks and Markov random fields, he is able to describe the relationships between random variables in these systems and to apply graph-based inference techniques to develop new algorithms. Among the algorithms described are the wake-sleep algorithm for unsupervised learning, the iterative turbodecoding algorithm (currently the best error-correcting decoding algorithm), the bits-back coding method, the Markov chain Monte Carlo technique, and variational inference.

Information

Save 30%

£56.40

£39.48

Download Now
Add to Basket
Sign in to add to wishlist

Information

Also in the Adaptive Computation and Machine Learning Series series

Machine Learning : A Probabilistic Perspective

Machine Learning

Kevin P. Murphy

£100.00

£63.89

Add to Basket
Reinforcement Learning : An Introduction

Reinforcement Learning

Richard S. (University of Alberta) Sutton

£95.00

£60.94

Add to Basket
Gaussian Processes for Machine Learning

Gaussian Processes for Machine Learning

Carl Edward (University of Cambridge) Rasmussen

£48.00

£33.16

Add to Basket
Introduction to Machine Learning

Introduction to Machine Learning

Ethem (Ozyegin University) Alpaydin

£80.00

£52.03

Add to Basket