Probabilistic machine learning : an introduction / Kevin P. Murphy.

Format:

Book

Author/Creator:

Murphy, Kevin P., 1970- author.

Contributor:

Class of 1924 Book Fund.

Series:

Adaptive computation and machine learning

Adaptive computation and machine learning series

Language:

English

Subjects (All):

Machine learning.

Probabilities.

Probability.

probability.

Medical Subjects:

Probability.

Physical Description:

xxix, 826 pages : illustrations (some color) ; 24 cm.

Place of Publication:

Cambridge, Massachusetts : The MIT Press, [2022]

Summary:

"This book provides a detailed and up-to-date coverage of machine learning. It is unique in that it unifies approaches based on deep learning with approaches based on probabilistic modeling and inference. It provides mathematical background (e.g. linear algebra, optimization), basic topics (e.g., linear and logistic regression, deep neural networks), as well as more advanced topics (e.g., Gaussian processes). It provides a perfect introduction for people who want to understand cutting edge work in top machine learning conferences such as NeurIPS, ICML and ICLR"-- Provided by publisher.

Notes:

Includes bibliographical references and index.

Local Notes:

Acquired for the Penn Libraries with assistance from the Class of 1924 Book Fund.

ISBN:

9780262046824

0262046822

OCLC:

1252413319