This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience.
The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.
- Format: Paperback
- Pages: 352 pages, illustrations
- Publisher: McGraw-Hill Education - Europe
- Publication Date: 01/10/1997
- Category: Machine learning
- ISBN: 9780071154673
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Review by IvanIdris
This is an introductory book on Machine Learning. There is quite a lot of mathematics and statistics in the book, which I like. A large number of methods and algorithms are introduced: Neural Networks Bayesian Learning Genetic Algorithms Reinforcement LearningThe material covered is very interesting and clearly explained. I find the presentation, however, a bit lacking. I think it has to do with the chosen fonts and lack of highlighting of important terms. Maybe it would have been better to have shorter paragraphs too.If you are looking for an introductory book on machine learning right now, I would not recommend this book, because in recent years better books have been written on the subject. These are better obviously, because they include coverage of more modern techniques. I give this book 3 out of 5 stars.