Articles liés à Probabilistic Machine Learning: Advanced Topics

Probabilistic Machine Learning: Advanced Topics - Couverture rigide

Murphy, Kevin P.

 
9780262048439: Probabilistic Machine Learning: Advanced Topics
Couverture rigide
ISBN 10 : 0262048434 ISBN 13 : 9780262048439
Editeur : The MIT Press, 2023

Synopsis

An advanced book for researchers and graduate students working in machine learning and statistics who want to learn about deep learning, Bayesian inference, generative models, and decision making under uncertainty.

An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics in machine learning, including deep generative modeling, graphical models, Bayesian inference, reinforcement learning, and causality. This volume puts deep learning into a larger statistical context and unifies approaches based on deep learning with ones based on probabilistic modeling and inference. With contributions from top scientists and domain experts from places such as Google, DeepMind, Amazon, Purdue University, NYU, and the University of Washington, this rigorous book is essential to understanding the vital issues in machine learning.

  • Covers generation of high dimensional outputs, such as images, text, and graphs 
  • Discusses methods for discovering insights about data, based on latent variable models 
  • Considers training and testing under different distributions
  • Explores how to use probabilistic models and inference for causal inference and decision making
  • Features online Python code accompaniment 

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l'auteur

Kevin P. Murphy is a Research Scientist at Google in Mountain View, California, where he works on artificial intelligence, machine learning, and Bayesian modeling.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
The MIT Press
Date d'édition
2023
Langue
anglais
ISBN 10 
0262048434
ISBN 13 
9780262048439
Reliure
Relié
Nombre de pages
1360
Coordonnées du fabricant
non disponible
Personne responsable
Easy Access System Europe
gpsr.requests@easproject.com

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