Introduction to Machine Learning (Adaptive Computation and Machine Learning series)

$65.00

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including

Quantity

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised learning; Bayesian decision theory; parametric, semi-parametric, and nonparametric methods; multivariate analysis; hidden Markov models; reinforcement learning; kernel machines; graphical models; Bayesian estimation; and statistical testing.

Machine learning is rapidly becoming a skill that computer science students must master before graduation. The third edition of Introduction to Machine Learning reflects this shift, with added support for beginners, including selected solutions for exercises and additional example data sets (with code available online). Other substantial changes include discussions of outlier detection; ranking algorithms for perceptrons and support vector machines; matrix decomposition and spectral methods; distance estimation; new kernel algorithms; deep learning in multilayered perceptrons; and the nonparametric approach to Bayesian methods. All learning algorithms are explained so that students can easily move from the equations in the book to a computer program. The book can be used by both advanced undergraduates and graduate students. It will also be of interest to professionals who are concerned with the application of machine learning methods.

Author

Ethem Alpaydin

Binding

Hardcover

EAN

9780262012430, 9780262028189

EANList

9780262012430, 9780262028189

Edition

Second Edition, Third Edition

ISBN

026201243X, 0262028182

IsEligibleForTradeIn

1

ItemDimensions

0, hundredths-inches, 0, hundredths-inches, 0, hundredths-pounds, 0, hundredths-inches, 126, hundredths-inches, 926, hundredths-inches, 269, hundredths-pounds, 824, hundredths-inches

Label

The MIT Press

Languages

English, Unknown, English, Original Language, English, Published

Manufacturer

The MIT Press

NumberOfItems

1

NumberOfPages

584, 640

ProductGroup

Book

PublicationDate

2009-12-04, 2014-08-29

Publisher

The MIT Press

Studio

The MIT Press

TradeInValue

1363, USD, $13.63, 2855, USD, $28.55