Can I read Machine Learning: A Bayesian and Optimization Perspective (Net Developers) on EtoBox?

Machine Learning: A Bayesian and Optimization Perspective (Net Developers) by Sergios Theodoridis is a nonfiction available to read on EtoBox.

What is Machine Learning: A Bayesian and Optimization Perspective (Net Developers) about?

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. All major classical techniques: Mean/Least-Squares regressio

Who reads Machine Learning: A Bayesian and Optimization Perspective (Net Developers)?

Author

Sergios Theodoridis

Publisher

Academic Press is an imprint of Elsevier

Published

2015

Language

EN

ISBN

9780128015223

Category

nonfiction

Subjects

Engineering, Science, Computer Science

Updated

2026-03-24