Machine Learning

Rating:
Summary: So - so
Review: This book is a good introduction to the field, but I think the notation can be quite cumbersome at times. I've seen the concepts presented elsewhere in less confusing form, but it's a good general source as it includes a considerable amount of information from relatively current research. The examples are typically very easy to understand, though they aren't always complicated enough to make the notation easy to understand.

Rating:
Summary: Great compilation
Review: This book is completely worth the price, and worth the hardcover to take care of it. The main chapters of the book are independent, so you can read them in any order. The way it explains the different learning approaches is beautiful because: 1)it explains them nicely 2)it gives examples and 3)it presents pseudocode summaries of the algorithms. As a software developer, what else could I possibly ask for?

Rating:
Summary: Excellent Introductory Text on ML
Review: This book serves as an excellent introduction to machine learning. The material covers a broad range of important machine learning concepts and algorithms. The text is well-written and well-organized, and I use it frequently as a reference. In addition to describing the basic theory and mechanics of the algorithms, the book helps develop an intuitive feel for the algorithms and provides examples of how they have been used.

That said, the coverage of the theory behind the algorithms is fairly superficial. Additionally, having been written in 1997, many recent algorithms such as SVMs and methods such as Adaboost are not covered. For those reasons, this book cannot serve as a stand-alone text book for a course.

Rating:
Summary: Excellent Introductory Text on ML
Review: This book serves as an excellent introduction to machine learning. The material covers a broad range of the important concepts and methods used in machine learning today. The text is well-written and well-organized, and I find myself frequently using it as a reference.

Rating:
Summary: The good textbook for beginning research
Review: This textbook is useful too much for students that need to learn about learning algorithms. In this textbook explains the key theory and algorithms to solve various problems. For student who plan to make a research in machine learning, this textbooks can give basic knowledge and background of the research.

Rating:
Summary: The best book for machine learning
Review: When I came to the field of machine learning, the book provides me a clear, easy-understanding picture to the field so that I believe any of you can get into the field by use of the book. If you are looking for your first book to this field, don't waste your time, it is. Even through my life in the research, I depended on it most of the time. It's too great.