Introduction to Machine Learning, 2 Edition



Ethem Alpaydin, "Introduction to Machine Learning, 2 Edition"
The M.I.T Press | 2010 | ISBN: 026201243X | 584 pages | File type: PDF | 3,1 mb

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. 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. New to the second edition are chapters on kernel machines, graphical models, and Bayesian estimation; expanded coverage of statistical tests in a chapter on design and analysis of machine learning experiments; case studies available on the Web (with downloadable results for instructors); and many additional exercises. All chapters have been revised and updated.

Introduction to Machine Learning can be used by advanced undergraduates and graduate students who have completed courses in computer programming, probability, calculus, and linear algebra. It will also be of interest to engineers in the field who are concerned with the application of machine learning methods.

Download links:

http://uploading.com/files/8bam6465/026201243XLearningMachine.rar/

http://depositfiles.com/files/xs5d1jjyo

http://www.filesonic.com/file/37127419/026201243XLearningMachine.rar


[Fast Download] Introduction to Machine Learning, 2 Edition


Related eBooks:
Screen Society
Learning Responsive Data Visualization
Malicious Attack Propagation and Source Identification
Robot Rules: Regulating Artificial Intelligence
Handbook of Research on Information and Cyber Security in the Fourth Industrial Revolution
Driving Traffic and Customer Activity Through Affiliate Marketing
R Graphics Cookbook: Practical Recipes for Visualizing Data, 2nd Edition
Itanium Architecture for Programmers: Understanding 64-Bit Processors and EPIC Principles
CCNP Routing and Switching TSHOOT 300-135 Official Cert Guide
Ecosystem Assessment and Fuzzy Systems Management
Cyber Spying Tracking Your Family's (Sometimes) Secret Online Lives
Designing Highly Useable Software
Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.