Description: A substantially revised fourth edition of a comprehensive textbook, including new coverage of recent advances in deep learning and neural networks.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
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End Time: 2024-09-23T12:58:39.000Z
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Publication Name: Introduction to Machine Learning (Adaptive Computation and Machin
Item Length: 9.4in
Publisher: MIT Press
Series: Adaptive Computation and Machine Learning Ser.
Publication Year: 2020
Type: Textbook
Format: Hardcover
Language: English
Item Height: 1.5in
Author: Ethem Alpaydin
Item Width: 8.3in
Item Weight: 51.6 Oz