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"Introduction to Machine Learning, Fourth Edition "

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"The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Machine learning underlies such exciting new technologies as self-driving cars, speech recognition, and translation applications. This substantially revised fourth edition of a comprehensive, widely used machine learning textbook offers new coverage of recent advances in the field in both theory and practice, including developments in deep learning and neural networks.

The book covers a broad array of topics not usually included in introductory machine learning texts, including supervised learning, Bayesian decision theory, parametric methods, semiparametric methods, nonparametric methods, multivariate analysis, hidden Markov models, reinforcement learning, kernel machines, graphical models, Bayesian estimation, and statistical testing. The fourth edition offers a new chapter on deep learning that discusses training, regularizing, and structuring deep neural networks such as convolutional and generative adversarial networks; new material in the chapter on reinforcement learning that covers the use of deep networks, the policy gradient methods, and deep reinforcement learning; new material in the chapter on multilayer perceptrons on autoencoders and the word2vec network; and discussion of a popular method of dimensionality reduction, t-SNE. New appendixes offer background material on linear algebra and optimization. End-of-chapter exercises help readers to apply concepts learned. Introduction to Machine Learning can be used in courses for advanced undergraduate and graduate students and as a reference for professionals."

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Detail Information

Series Title

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Call Number

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Publisher

Hardcover : Publisher: The MIT Press., 2020

Collation

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Language

English

ISBN/ISSN

9780262043793

Classification

NONE

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

1

Subject(s)

MACHINE

Specific Detail Info

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Statement of Responsibility

Ethem Alpaydın

Other Information

Cataloger

Suwardi

Source

https://mitpress.mit.edu/9780262043793/introduction-to-machine-learning/

Validator

Suwardi

Digital Object Identifier (DOI)

https://mitpress.mit.edu/9780262043793/introduction-to-machine-learning/

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