An Introduction to Machine Learning Pdf This publication presents basic notions of machine learning in a means that’s not hard to comprehend, by supplying hands-on practical information, using straightforward illustrations, and inspiring students with talks of interesting software. The principal issues include Bayesian classifiers, nearest-neighbor classifiers.
linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to unite these easy tools by means of “fostering,” the way to use them in much more complex domains, and also how to manage varied advanced practical difficulties. 1 chapter is devoted to the genetic algorithms that are popular.
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