Probabilistic Machine Learning

Name: Probabilistic Machine Learning
Brand: MIT Press Ltd
SKU: 9780262048439
Price: 4038 CZK
Availability: InStock

Advanced Topics

Autor: Kevin P. Murphy

Jazyk:

Vazba: Pevná

Vydavatel: MIT Press Ltd

Dostupnost: Skladem u dodavatele

Odesíláme za 14-17 dnů

4 038 Kč

An advanced book for researchers and graduate students working in machine learning and statistics wh...

Informace o knize

Autor

Kevin P. Murphy

Jazyk

Angličtina

Vazba

Kniha - Pevná

Vydáno

2023

Stránek

1360

EAN

9780262048439

Enbook ID

43194552

Vydavatel

MIT Press Ltd

Hmotnost

2020

Rozměry

203 x 229

Kompletní 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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Probabilistic Machine Learning

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Kompletní popis

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