Probabilistic Machine Learning: An Introduction

By:

Murphy, Kevin P [autor]

Material type: Text

TextLanguage: English Publisher: : Massachusetts Institute of Technology, 2022Edition: 1a. edDescription: 826 páginas; ImpresoContent type:

texto

Media type:

no mediado

Carrier type:

volumen

ISBN:

978-0-262-04682-4

Subject(s):

DDC classification:

006.3 M9781

Abstract: 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.

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Holdings
Item type	Current library	Shelving location	Call number	Status	Barcode
Libro	Biblioteca Hernán Malo González	Biblioteca Central Bloque A	006.3 M9781 BG18488 (Browse shelf(Opens below))	Available	BG18488

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.

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