By Miroslav Kubat
This textbook offers primary laptop studying strategies in a simple to appreciate demeanour through offering useful suggestion, utilizing ordinary examples, and supplying attractive discussions of correct functions. the most issues contain Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, determination bushes, neural networks, and help vector machines. Later chapters convey find out how to mix those easy instruments when it comes to “boosting,” tips on how to take advantage of them in additional complex domain names, and the way to accommodate assorted complicated useful concerns. One bankruptcy is devoted to the preferred genetic algorithms.
This revised version includes 3 totally new chapters on serious issues concerning the pragmatic software of computer studying in undefined. The chapters learn multi-label domain names, unsupervised studying and its use in deep studying, and logical methods to induction. a variety of chapters were elevated, and the presentation of the cloth has been better. The ebook includes many new workouts, a number of solved examples, thought-provoking experiments, and machine assignments for self reliant work.
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Extra resources for An Introduction to Machine Learning
An Introduction to Machine Learning by Miroslav Kubat