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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.
- Sales Rank: #196544 in Books
- Published on: 1997-10-01
- Original language: English
- Number of items: 1
- Dimensions: 9.49" h x 1.30" w x 6.57" l, .0 pounds
- Binding: Paperback
- 414 pages
Most helpful customer reviews
3 of 3 people found the following review helpful.
Great Overview Book, Spine cracks...
By emoKid
This book is really good for an introduction to all types of machine learning algorithms. It has good detail for most of the algorithms.
Some of the other reviewers say that it lacks depth. This is somewhat true. There are a few chapters that leave you wanting more, but overall I still think this is a good book.
I have several machine learning books, and most of them are more in depth, but lacking a broader overview of machine learning. So if you want an overview of different problem solving techniques, this is the book for you. It has enough theory to keep most people happy. If you want to know the core motivational aspect to the finest details, this book will be lacking in some areas. Other books may have more detail, but just know they won't cover as much of the overall subject.
This is always my go to book for trying to remember something. It's small, light, and enough to get me back on track. I have other books for more in depth reading, but they don't cover as much of the subject of machine learning as this one.
3 of 3 people found the following review helpful.
Excellent, but the price?
By Rafael Espericueta
But for the excessive price, I would have given this text five stars.
Another excellent text on machine learning is Pattern Recognition and Machine Learning - twice as much material with beautiful color diagrams (the Mitchell text is just B/W), and for less than half the price.
1 of 1 people found the following review helpful.
Solid and accessible intro to the topic. Might be ...
By Amazon Customer
Solid and accessible intro to the topic. Might be a bit dated. Could be more concise, but readers without a strong math background might appreciate the lengthy examples and introductions. Mitchell holds your hand through some of the hairier derivations where denser texts might omit explanations or completely skip steps.
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