Kniha Probabilistic Machine Learning Kevin P. Murphy

Probabilistic Machine Learning

Advanced Topics

Jazyk: Angličtina
Väzba: Pevná
Vydavateľ: MIT Press Ltd
Dostupnosť: Skladom u dodávateľa
Odosielame za 14-17 dní
166.93
An advanced book for researchers and graduate students working in machine learning and statistics wh...

Informácie o knihe

Jazyk
Angličtina
Väzba
Kniha - Pevná
Vydalo
2023
Stránok
1360
EAN
9780262048439
Enbook ID
43194552
Vydavateľ
Hmotnosť
2020
Rozmery
203 x 229

Kompletný popis

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

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