Description

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Offers frequent opportunities to practice techniques with control questions, exercises, thought experiments, and computer assignments.

Reinforces principles using well-selected toy domains and relevant real-world applications.

Provides additional material, including an instructor's manual with presentation slides, as well as answers to exercises.

About the Author

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Miroslav Kubat, Associate Professor at the University of Miami, has been teaching and studying machine learning for over 25 years. He has published more than 100 peer-reviewed papers, co-edited two books, served on the program committees of over 60 conferences and workshops, and is an editorial board member of three scientific journals. He is widely credited with co-pioneering research in two major branches of the discipline: induction of time-varying concepts and learning from imbalanced training sets. He also contributed to research in induction from multi-label examples, induction of hierarchically organized classes, genetic algorithms, and initialization of neural networks.