You are here

Back to top

Machine Learning: A Bayesian and Optimization Perspective (Net Developers) (Hardcover)

Machine Learning: A Bayesian and Optimization Perspective (Net Developers) Cover Image
Email or call for price.
Out of Print


This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches -which are based on optimization techniques - together with the Bayesian inference approach, whose essence lies in the use of a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts.

The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as short courses on sparse modeling, deep learning, and probabilistic graphical models.

Product Details
ISBN: 9780128015223
ISBN-10: 0128015225
Publisher: Academic Press
Publication Date: March 27th, 2015
Pages: 1062
Language: English
Series: Net Developers