Excellent treatment of a difficult subject

books:


	• Pattern Recognition and Machine Learning (Information Science and Statistics) Christopher M. Bishop Springer, 2007 - 738 pages average customer review:based on 41 reviews view larger image
	for more information click here

highly recommended

Excellent Reference

As a graduate student doing research in Computer Vision, I have found Bishop's book to be an excellent reference. I purchased the book to help myself pick up some important techniques that were never covered in my formal coursework. I certainly haven't read it in its entirety yet, but have read many sections and am impressed with the explanations given. The book covers a broad spectrum of topics (just what I wanted in that regard), some complicated, and does so in a pleasantly clear and intuitive manner. I also found the brief biographies on mathematicians I've heard of over the years very interesting. Overall, an excellent reference!

for more information click here

Excellent treatment of a difficult subject

Bishop does an excellent job of conveying an intuitive understanding of a wide and complex range of topics. Where so many authors just present theorems and proofs, this book goes to the trouble of showing graphically what is going on with the various problems and techniques described. If you are among the target audience specified in the "Book Description" (advanced undergraduate upwards) you should be able to follow the notation; and you will not be disappointed to discover that "this is a textbook" because the description clearly states that it is!

for more information click here

recommend for non statistics majors

I started to read this book after I gave up the book "element of statisitcal learning" which I read about 80 pages. I won't say that the latter book EoSL is bad, but it definitely assumes a much higher math background. Also it doesn't give all the derivations and reasonings, so it may take a long time to understand a single paragraph. The reading is slow and frustrating. I read each chapter twice, but still do not think I did get it in my heart.

By contrast, the book "Pattern Recognition and machine learning" assumes much less math background, and usually gives complete derivation and reasoning, which makes it a pleasure to read. Therefore, if you are not in statistics major (but a CS major with reasonable statistics background), I recommend you to start this book.
Answers to some problems are posted in the author's website (just google the author's name). It is a big plus to me.

for more information click here

reviews: 1, 2, 3, 4, 5, 6, page 7, 8, 9

hot

not?

What's your opinion?

Write a review and share your thoughts!

recommendations

Probabilistic Graphical Models
Theoretical Computer Science
Learn machine learning
Applied Statistics
My Books

search for books
information, learning, machine, pattern, recognition, science, statistics

Impressum / about us