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Machine Learning (McGraw-Hill Series in Computer Science) (Hardcover)

by Thomas Mitchell (Author) "Ever since computers were invented, we have wondered whether they might be made to learn ..." (more)

5.0 out of 5 stars See all reviews (3 customer reviews)

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Pattern Recognition and Machine Learning (Information Science and Statistics) (Information Science and Statistics) by Christopher M. Bishop

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This item: Machine Learning (McGraw-Hill Series in Computer Science) by Thomas Mitchell
In stock.
Dispatched from and sold by Amazon.co.uk.
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Pattern Recognition and Machine Learning (Information Science and Statistics) (Information Science and Statistics) by Christopher M. Bishop
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Product details

Hardcover: 432 pages
Publisher: McGraw-Hill Higher Education (4 Jul 1997)
Language English
ISBN-10: 0070428077
ISBN-13: 978-0070428072
Product Dimensions: 23.6 x 16.6 x 2 cm

Average Customer Review: 5.0 out of 5 stars See all reviews (3 customer reviews)

Amazon.co.uk Sales Rank: 609,253 in Books (See Bestsellers in Books)

Popular in these categories:

#54 in	Books > Computing & Internet > Computer Science > Algorithms > Machine Learning
#61 in	Books > Computing & Internet > Computer Science > Artificial Intelligence > Machine Learning
#72 in	Books > Science & Nature > Popular Science > Artificial Intelligence

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Product Description

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.

Book Description

The broad basics covers the concepts and techniques that contribute to the field of machine learning. Details the valuable logical components of decision tree learning as a useful technique to create logical conclusion of processes. Incorporates a variety of basic research from an array of computer scientists. Offers several alternative approaches to the subject.

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Inside This Book (Learn More)

First Sentence
Ever since computers were invented, we have wondered whether they might be made to learn. Read the first page

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	72% buy the item featured on this page: Machine Learning (McGraw-Hill Series in Computer Science) 5.0 out of 5 stars (3) �103.04
	9% buy Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (The Morgan Kaufmann Series in Data Management Systems) 5.0 out of 5 stars (1) �29.67
	8% buy Pattern Recognition and Machine Learning (Information Science and Statistics) (Information Science and Statistics) 4.3 out of 5 stars (7) �48.34
	6% buy Artificial Intelligence: A Modern Approach (International Edition) 3.8 out of 5 stars (12) �49.39

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Customer Reviews

3 Reviews

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5.0 out of 5 stars (3 customer reviews)

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Most Helpful Customer Reviews

7 of 7 people found the following review helpful:

5.0 out of 5 stars Excellent overview of all major machine learning topics., 16 Jul 1999

By A Customer

I first used this book as the required text for my course in ML in 1997 and got rave reviews from the students. I will be using it again in 1999. I found ALL of the major topics and issues in ML addressed. The book is easily readable with anyone with a computer science background, and the book works quite well in a wide variety of approaches to presentation at the advanced undergraduate and graduate levels.

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6 of 15 people found the following review helpful:

5.0 out of 5 stars Complete Coverage of the topic, 20 May 2001

By	Oli (United Kingdom) - See all my reviews

This review is from: MACHINE LEARNING (Mcgraw-Hill International Edit) (Paperback)

Covers Machine Learning concepts thoroughly, allowing you to decide which type is best for any particular problem. Uses some daunting mathematical notation, but still easy to follow

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1 of 3 people found the following review helpful:

5.0 out of 5 stars This book has proselytized me!!!!, 10 May 1999

By A Customer

Everything I will do in the future will be based on ML and just one semester of an ML course & this book has converted me(even though my major is not Comp.Science). Of-course this is due majorly to Dr. Thomas Ioerger and his teaching abilities(Texas A&M), but the book presents all concepts(even seemingly complex ones) in a way that is easy and enjoyable to learn. One of the most useful books I've ever studied!

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