Probabilistic Machine Learning
An Introduction
$231.03
- Hardcover
944 pages
- Release Date
1 March 2022
Summary
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.
This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression …
Book Details
| ISBN-13: | 9780262046824 |
|---|---|
| ISBN-10: | 0262046822 |
| Author: | Kevin P. Murphy |
| Publisher: | MIT Press Ltd |
| Imprint: | MIT Press |
| Format: | Hardcover |
| Number of Pages: | 944 |
| Release Date: | 1 March 2022 |
| Weight: | 1.05kg |
| Dimensions: | 229mm x 203mm |
| Series: | Adaptive Computation and Machine Learning series |
You Can Find This Book In
About The Author
Kevin P. Murphy
Kevin P. Murphy is a Research Scientist at Google in Mountain View, California, where he works on AI, machine learning, computer vision, and natural language understanding.
Returns
This item is eligible for free returns within 30 days of delivery. See our returns policy for further details.