An Introduction To Machine Learning by Miroslav KubatAn Introduction To Machine Learning by Miroslav Kubat

An Introduction To Machine Learning

byMiroslav Kubat

Paperback | October 15, 2016

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This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way of "boosting," how to exploit them in more complicated domains, and how to deal with diverse advanced practical issues. One chapter is dedicated to the popular genetic algorithms.

Miroslav Kubat, Associate Professor at the University of Miami, has been teaching and studying machine learning for more than a quarter century. Over the years, he has published more than 100 peer-reviewed papers, co-edited two books, served on the program committees of some 60 program conferences and workshops, and is the member of th...
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Title:An Introduction To Machine LearningFormat:PaperbackDimensions:291 pages, 23.5 × 15.5 × 0.17 inPublished:October 15, 2016Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3319348868

ISBN - 13:9783319348865

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Table of Contents

A Simple Machine-Learning Task.- Probabilities: Bayesian Classifiers.- Similarities: Nearest-Neighbor Classifiers.- Inter-Class Boundaries: Linear and Polynomial Classifiers.- Artificial Neural Networks.- Decision Trees.- Computational Learning Theory.- A Few Instructive Applications.- Induction of Voting Assemblies.- Some Practical Aspects to Know About.- Performance Evaluation.-Statistical Significance.- The Genetic Algorithm.- Reinforcement learning.