Free shipping on all orders over $79* Limited Time Only
Track My Order
Help Centre
Likes
My Wish ListsLogin / Join
Booktopia
Australia's local bookstore
Get Free Shipping on orders over $79
Probabilistic Machine Learning : Advanced Topics - Kevin P. Murphy

Probabilistic Machine Learning

Advanced Topics

By: Kevin P. Murphy

eText | 15 August 2023

At a Glance

eText

$151.31

or 4 interest-free payments of $37.83 with

 or 

Instant online reading in your Booktopia eTextbook Library *

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

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
on
Desktop
Tablet
Mobile

You Can Find This eBook In

Non-FictionComputing & I.T.Computer ScienceArtificial IntelligenceMachine Learning

Other Editions and Formats

Hardcover

Published: 3rd October 2025

View Product

More in Computer Science

Amazon.com : Get Big Fast - Robert Spector

eBOOK

Amazon.com

Get Big Fast

eBook

$22.99

Gene Expression Analysis : Methods and Protocols - Nalini Raghavachari

eBOOK

Gene Expression Analysis

Methods and Protocols

eBook

RRP $369.00

$332.99

10%
OFF

This product is categorised by