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12 Reviews
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4 of 4 people found the following review helpful
5.0 out of 5 stars The Machine learning Book
Although it's expensive book I think it worth the money as it is the "Bible" of Machine Learning and Pattern recognition. However, has a lot of mathematics meaning that a strong mathematical background is necessary. I suggest it especially for PhD candidates in this field.
Published 18 months ago by Spiros

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39 of 47 people found the following review helpful
3.0 out of 5 stars Great insights, but a hard read
This new book by Chris Bishop covers most areas of pattern recognition quite exhaustively. The author is an expert, this is evidenced by the excellent insights he gives into the complex math behind the machine learning algorithms. I have worked for quite some time with neural networks and have had coursework in linear algebra, probability and regression analysis, and...
Published on 14 Jun 2007 by Sidhant


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4 of 4 people found the following review helpful
5.0 out of 5 stars The Machine learning Book, 27 Jun 2013
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This review is from: Pattern Recognition and Machine Learning (Information Science and Statistics) (Hardcover)
Although it's expensive book I think it worth the money as it is the "Bible" of Machine Learning and Pattern recognition. However, has a lot of mathematics meaning that a strong mathematical background is necessary. I suggest it especially for PhD candidates in this field.
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3 of 3 people found the following review helpful
5.0 out of 5 stars Outstanding book, 16 Mar 2009
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Luciano Oliveira "powdersama" (Coimbra, Portugal) - See all my reviews
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This review is from: Pattern Recognition and Machine Learning (Information Science and Statistics) (Hardcover)
This is an outstanding book. The author did not neglect any aspect for a good explanation and even a undergraduate student can follow the points in the book. Even though, the book covers as much an introductory view as a more advanced math in a considerable detail, in a clean and simple way. I totally recommend this book.
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7 of 8 people found the following review helpful
5.0 out of 5 stars Great Textbook and Reference, 5 Mar 2009
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Prepaid "Dimitrios Bouzas" (Greece) - See all my reviews
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This review is from: Pattern Recognition and Machine Learning (Information Science and Statistics) (Hardcover)
For people that are interested in machine learning this is a must. Not dry and colorful, I really enjoyed the small boxes with the biographies of the great mathematicians, very cool idea.

Advices:
1) Mathematical background in advanced calculus and linear algebra is required.
2) Basic background in statistics and probability will make the chapters more comprehensible, but if you don't have it, don't despair. The author gives an overview of the required statistical and probabilistic tools in the first chapters and in the appendices.
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39 of 47 people found the following review helpful
3.0 out of 5 stars Great insights, but a hard read, 14 Jun 2007
This review is from: Pattern Recognition and Machine Learning (Information Science and Statistics) (Hardcover)
This new book by Chris Bishop covers most areas of pattern recognition quite exhaustively. The author is an expert, this is evidenced by the excellent insights he gives into the complex math behind the machine learning algorithms. I have worked for quite some time with neural networks and have had coursework in linear algebra, probability and regression analysis, and hence found some of the stuff in the book quite illuminating.

But that said, I must point out that the book is very math heavy. Inspite of my considerable background in the area of neural networks, I still was struggling with the equations. This is certainly not the book that can teach one things from the ground up, and thats why I would give it only 3 stars. I am new to kernels, and I am finding the relevant chapters quite confusing. For those who want to build powerful machine learning solutions to their problems, I am sorry but they will have to look elsewhere. This book cant help you build an application, another serious drawback in my opinion. The intended audience for this book I guess are PhD students/researchers who are working with the math related aspects of machine learning, and not undergraduates or working professionals who want to write machine learning code for their applications/projects.
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2 of 2 people found the following review helpful
5.0 out of 5 stars a reference in the domain of machine learning, 31 Oct 2013
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This review is from: Pattern Recognition and Machine Learning (Information Science and Statistics) (Hardcover)
a reference in the domain of machine learning ... plus the quality of the paper used, the colors .... everything makes this book a must have if you are interested in machine learning
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13 of 16 people found the following review helpful
5.0 out of 5 stars Excellent book, 28 Jan 2007
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Andrea Prati (Modena, Italy) - See all my reviews
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This review is from: Pattern Recognition and Machine Learning (Information Science and Statistics) (Hardcover)
As a newbie to pattern recognition I found this book very helpful. It is the clearest book I ever read! Accompanying examples and material are very illuminating. I particularly appreciated the gradual introduction of key concepts, often accompanied with practical examples and stimulating exercises.
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7 of 9 people found the following review helpful
5.0 out of 5 stars Best book of its kind I have found, 24 Mar 2007
By 
Amazon Customer (Cambridge, England) - See all my reviews
This review is from: Pattern Recognition and Machine Learning (Information Science and Statistics) (Hardcover)
Bishop does an excellent job of helping the reader visualize what is going on in the problems and techniques he describes, emphasizing an intuitive grasp of the issues without sacrificing mathematical rigour. The writing is clear and the production is excellent. Strongly recommended both for anyone serious about getting into machine learning and for those already working in it.
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6 of 8 people found the following review helpful
2.0 out of 5 stars Not a book for beginners!, 22 Nov 2011
This review is from: Pattern Recognition and Machine Learning (Information Science and Statistics) (Hardcover)
The book is a note collection for people who already have the understanding. The book is based on 'learning through equations' but lack examples. For instance the Hidden markov models is much better explained by Lawrence Rabiner.
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4.0 out of 5 stars Good in-depth book, 6 May 2014
By 
DLP (Bristol, UK) - See all my reviews
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This review is from: Pattern Recognition and Machine Learning (Information Science and Statistics) (Hardcover)
This is a good in-depth book on pattern recognition. The only problem I have with it is that it can be a challenge to read. I find it easier to understand new mathematical techniques and equations when they come coupled with a good intuitive explanation for people who find it harder to just look at an equation and instantly "get it". I find that this book isn't as good at this as I would like, but it is so full of useful information that it's still a great book.
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1 of 2 people found the following review helpful
4.0 out of 5 stars Great Book for mid-adv level students, 2 Aug 2009
By 
E. M. Massey "That Beth Chick" (Lincoln, Lincolnshire UK) - See all my reviews
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This review is from: Pattern Recognition and Machine Learning (Information Science and Statistics) (Hardcover)
This book is worth whatever you pay for it and I strongly recommend having it in your reference library, esepcially if your field is pattern recognition, computer vision, or neural networks. This book does a good job explaining concepts and gives relevant mathematical insights. It is not, however, written as a tutorial - which in some cases would have been helpful. Also, a bit of code or psuedocode now again would be nice. Otherwise, an outstanding book.
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