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- Title Introduction to Machine Learning
- Author(s) Alex Smola, S.V.N. Vishwanathan
- Publisher: Cambridge University Press (2008); eBook (October 1, 2010)
- Hardcover/Paperback ?
- eBook PDF (234 pages, 10.3 MB)
- Language: English
- ISBN-10: 0521825830
- ISBN-13: N/A
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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. 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.
This book is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. In order to present a unified treatment of machine learning problems and solutions, it discusses many methods from different fields, including statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and data mining.
All learning algorithms are explained so that the student can easily move from the equations in the book to a computer program. The text covers such topics as supervised learning, Bayesian decision theory, parametric methods, multivariate methods, multilayer perceptrons, local models, hidden Markov models, assessing and comparing classification algorithms, and reinforcement learning.About the Authors
- Machine Learning
- Artificial Intelligence
- Data Analysis and Data Mining
- Neural Networks
- Statistics, R Language and SAS Programming
- Operations Research (OR), Linear Programming, Optimization, and Approximation
- Introduction to Machine Learning (Alex Smola, et al)
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