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Probabilistic Machine Learning: An Introduction.

Probabilistic Machine Learning: An Introduction


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ISBN: 9780262046824 | 864 pages | 22 Mb
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  • Probabilistic Machine Learning: An Introduction
  • Page: 864
  • Format: pdf, ePub, fb2, mobi
  • ISBN: 9780262046824
  • Publisher: MIT Press
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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 and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.

Probabilistic Machine Learning for Civil Engineers - The MIT
An introduction to key concepts and techniques in probabilistic machine learning for civil engineering students and professionals; with many step-by-step 
Probabilistic Machine Learning
Mar 1, 2022 — Probabilistic Machine Learning. An Introduction. Kevin P. Murphy. A comprehensive undergraduate-level introduction integrating.2 pages
Probabilistic Machine Learning by Kevin P. Murphy - Penguin
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.Format: HardbackRRP: $195.00Published: 22 February 2022
Probabilistic Machine Learning eBook by Kevin P. Murphy
Read "Probabilistic Machine Learning An Introduction" by Kevin P. Murphy available from Rakuten Kobo. A detailed and up-to-date introduction to machine 
Machine Learning | Guide books - ACM Digital Library
This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.

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