An Introduction to Machine Learning 3rd Edition by Miroslav Kubat ISBN 3030819353 9783030819354

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Product details:

ISBN 10: 3030819353

ISBN 13: 9783030819354

Author:  Miroslav Kubat 

An Introduction to Machine Learning 3rd Edition: 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.

 

An Introduction to Machine Learning 3rd Edition Table of contents:

1. Ambitions and Goals of Machine Learning

2. Probabilities: Bayesian Classifiers

3. Similarities: Nearest-Neighbor Classifiers

4. Inter-Class Boundaries: Linear and Polynomial Classifiers

5. Decision Trees

6. Artificial Neural Networks

7. Computational Learning Theory

8. Experience from Historical Applications

9. Voting Assemblies and Boosting

10. Classifiers in the Form of Rule-Sets

11. Practical Issues to Know About

12. Performance Evaluation

13. Statistical Significance

14. Induction in Multi-label Domains

15. Unsupervised Learning

16. Deep Learning

17. Reinforcement Learning: N-Armed Bandits and Episodes

18. Reinforcement Learning: From TD(0) to Deep-Q-Learning

19. Temporal Learning

20. Hidden Markov Models

21. Genetic Algorithm

 

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