Skip to content
Description
By: Kevin P. Murphy | Series: Adaptive Computation and Machine Learning series
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.
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
You may also like
Top Trending
Press Start! #17 The Super Jump Between Worlds! (Branches)
Sale priceHK$55.00
Regular priceHK$98.00
In stock
Dog Man 14: Dog Man: Big Jim Believes: A Graphic Novel (Dog Man #14)
Sale priceHK$85.00
Regular priceHK$150.00
In stock
Billy and the Mini Monsters: Monsters Play Football
Sale priceHK$59.00
Regular priceHK$98.00
In stock
Anzu and the Realm of Darkness: A Graphic Novel
Sale priceFrom HK$85.00
Regular priceHK$140.00
In stock
Darkstalker: A Graphic Novel (Wings of Fire: Legends Graphic Novel)
Sale priceHK$99.00
Regular priceHK$154.00
In stock
