The Elements of Statistical Learning
The Elements of Statistical Learning

The Elements of Statistical Learning

Manufacturer:
Springer Verlag

UPC:
978038795284

Retail Price:
$89.95

#Deals:

Avg. Rating:

Available from 8 stores - Select your deal and buy the The Elements of Statistical Learning
"Where can I buy a The Elements of Statistical Learning?" At all of these merchants listed below. Click any of the deals below to buy now on the merchant's website.
StoreRatingBase PriceShipping Price + ShippingAvailability
best_bargain_books3

[Store Info & Reviews]
Covered by A-Z Guarantee
5 Star Rating
600 Reviews
$13.19
New
$3.99
$17.18Buy from best_bargain_books3
In Stock. Usually ships in 1-2 business days
48 Available
opoebooks

[Store Info & Reviews]
Covered by A-Z Guarantee
5 Star Rating
400 Reviews
$56.40
New
$3.99
$60.39Buy from opoebooks
In Stock. Usually ships in 1-2 business days
18 Available
SHIPS FAST! via UPS(AK/HI Priority Mail) within 24 hours/ NEW book
Any_Book

[Store Info & Reviews]
Covered by A-Z Guarantee
5 Star Rating
1100 Reviews
$71.03
New
$3.99
$75.02Buy from Any_Book
In Stock. Usually ships in 1-2 business days
Just 3 Left!
Brand New!Satisfaction Guaranteed!
planet_books

[Store Info & Reviews]
Covered by A-Z Guarantee
5 Star Rating
64 Reviews
$74.00
New
$3.99
$77.99Buy from planet_books
In Stock. Usually ships in 1-2 business days
10 Available
BestBookDepot

[Store Info & Reviews]
Covered by A-Z Guarantee
5 Star Rating
207 Reviews
$76.74
New
$3.99
$80.73Buy from BestBookDepot
In Stock. Usually ships in 1-2 business days
Just 1 Left!
***NEW UNREAD/UNUSED*** Bookstore overstock. Multiple copies available. May have small overstock mark along edge. Buy with confidence. Immediate processing. Prompt shipping. Excellent service. Thank you for your purchase!
woodys-books

[Store Info & Reviews]
Covered by A-Z Guarantee
5 Star Rating
4602 Reviews
$78.59
New
$3.99
Expedited Shipping is available Expedited Available
$82.58Buy from woodys-books
In Stock. Usually ships in 1-2 business days
Just 1 Left!
Excellent customer service. May ship from alternate location depending on your zip code and availability. Satisfaction guaranteed!!
outlook_books

[Store Info & Reviews]
Covered by A-Z Guarantee
5 Star Rating
1132 Reviews
$14.19
New
See Site
See SiteBuy from outlook_books
In Stock. Usually ships in 1-2 business days
Just 2 Left!
surpluscomputerbooks

[Store Info & Reviews]
Covered by A-Z Guarantee
5 Star Rating
331 Reviews
$76.73
New
See Site
See SiteBuy from surpluscomputerbooks
In Stock. Usually ships in 1-2 business days
Just 5 Left!
* Shipping estimates are based on Ground shipment within the contiguous U.S.
   If you notice a problem, you can report a pricing error or problem.
Overview of current deals for the The Elements of Statistical Learning:
  • 1 merchant has Express Shipping options.
The Elements of Statistical Learning Specs:
Product NameThe Elements of Statistical Learning
ManufacturerSpringer Verlag
Product Number MPN0387952845
Retail Price $89.95
EAN-1409780387952840
UPC978038795284
EAN-139780387952840
Specifications 
TitleThe Elements of Statistical Learning
ISBN0387952845
Author(s)T. Hastie, R. Tibshirani, J. H. Friedman
Release Date09 August, 2001, 2003-07-30, 2001-08-09
FormatHardcover
Num of Pages552
Num. of Items1
EAN9780387952840
EditionCorrected
Dimensions9.3 x 6.4 x 1.2 in.
Weight0.5 lbs.
Deal first added on:26-January-2004

Tags

Find other products that have similar tags to the The Elements of Statistical Learning
Computers mathematics Probability & Statistics - General Computer Bks - General Information Artificial Intelligence - General Database Management - Database Mining Regression analysis Neural Computing Supervised learning (Machine l
Similar Products
Pattern Recognition and Machine Learning (Information Science and Statistics)Pattern Recognition and Machine Learning (Information Science and Statistics)84.95$51.00Check Prices on Pattern Recognition and Machine Learning (Information Science and Statistics)
at 9 stores
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)65.95$32.49Check Prices on Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
at 5 stores
Pattern Classification (2nd Edition)Pattern Classification (2nd Edition)140.00$69.38Check Prices on Pattern Classification (2nd Edition)
at 9 stores
All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics)All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics)89.95$65.31Check Prices on All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics)
at 9 stores
Gödel, Escher, Bach: An Eternal Golden BraidGödel, Escher, Bach: An Eternal Golden Braid22.95$12.00Check Prices on Gödel, Escher, Bach: An Eternal Golden Braid
at 9 stores
The Mythical Man-Month: Essays on Software Engineering, 20th  Anniversary EditionThe Mythical Man-Month: Essays on Software Engineering, 20th Anniversary Edition39.99$17.94Check Prices on The Mythical Man-Month: Essays on Software Engineering, 20th  Anniversary Edition
at 7 stores

Accessories
Monte Carlo Statistical MethodsMonte Carlo Statistical Methods89.95$74.55Check Prices on Monte Carlo Statistical Methods
at 8 stores
Latest 6 Reviews
Here is what people are saying about the The Elements of Statistical Learning
4 Star Rating  "authoritative textbook for data mining"2009-06-22
- Reviewed By User: A20DXHZ8PSN643
This edition adds some essential features for supervised statistical learning, such as supervised principle components, which I find fairly useful.
 
1 Star Rating  "Not the best textbook for a class"2009-04-14
- Reviewed By stf481982
I used this book for my stats course. While I do enjoy reading some of the parts of the book, I have to say that I am rather dissappointed with the presentation in the book.

1. This book assumes that you already have some background and quite a bit of familiarity with the subject

2. While it contains many topics, most materials are only "presented" rather than "clearly explained". And so, while it may be good as a reference book, at least for me, this definitely shouldn't be your main resource when first studying the subject.

3. Definitely the authors are expert on the field and I just hope they would come up with a much better revision of the book

4. One nice feature of the book ... it contains pretty picture! Unfortunately, just like the old saying, "a picture contains a thousand words". Thats exactly what happens here. Some of the pictures are hard to understand.

It may or may not be fair to give this book 1 star (I might update my rating in the future). But the simple truth is that I am not impressed when I first read the book. It surely falls below my expectation from such a highly acclaimed book.


 
4 Star Rating  "Has the most post-its of any book on my shelf"2009-04-04
- Reviewed By User: AAG19DPW2P2X4
This is one of the best books in a difficult field to survey and summarize. Like 'Pattern Recognition', 'Statistical Learning' is an umbrella term for a broad range of techniques of varying complexity, rigor and acceptance by practitioners in the field. The audience for such a text ranges from the user requiring a code library to the mathematician seeking proof of every statement. I sit somewhere in the middle, but more towards the mathematical end. I subscribe to the traditional statistician's view of Machine Learning. It is a term invented in order to avoid having to prove theorems and dodge the rigors of 'real' statistics. However, I strongly support such a course of action. There is an immense need for Machine Learning algorithms, whether they have actual properties or not, and an equal need for books to introduce these topics to people like myself who have a strong mathematical background, but have not been exposed to these techniques.

Hastie & Tibshirani has the most post-it's of any book on my shelf. When my company built an custom multivariate statistical library for our targeted product, we largely followed Hastie & Tibshirani's taxonomy. Their overview of support vector machines is excellent, and I found little of value to me in dedicated volumes like Cristianini & Shawe-Taylor that wasn't covered in Hastie & Tibshirani. Hastie & Tibshirani is another book with excellent visual aides. In addition to some great 2-D representations of complex multidimensional spaces, I thought the 'car going up hill' icon was a very useful cue that the level was going up a notch.

Having praised this book, I can't argue with any of the negative reviews. There is no right answer of where to start or what to cover. This book will be too mathematical for some, insufficiently rigorous for others, but was just right for me. It will offer too much of a hodge-podge of techniques, miss someone's favorite, or offer just the right balance. In the end, it was the best one for me, so if you're like me (someone with a very solid math base, not a mathematician, who appreciates rigor, but isn't married to it, and who is looking to self-start on this topic.) you'll like it.
 
5 Star Rating  "my big brown book of statistic learning tools"2009-03-22
- Reviewed By seanmatthews
This is a quite interesting, and extremely useful book, but it is wearing to read in large chunks. The problem, if you want to call it that, is that it is essentially a 700 page catalogue of clever hacks in statistical learning. From a technical point of view it is well-ehough structured, but there is not the slightest trace of an overarching philosophy. And if you don't actually have a philosophical perspective in place before you start, the read you face might well be an even harder grind. Be warned.

Some of the reviews here complain that there is too much math. I don't think that is an issue. If you have decent intuitions in geometry, linear algebra, probability and information theory, then you should be able to cruise through and/or browse in a fairly relaxed way. If you don't have those intuitions, then you are attempting to read the wrong book.

There were a couple of things that I expected (things I happen to know a bit about), but that were missing. On the unsupervised learning side, the discussion of Gaussian mixture clustering was, I thought, a bit short and superficial, and did not bring out the combination of theoretical and practical power that the method offers. On the supervised learning side, I was surprised that a book that dedicates so much time to linear regression finds no room for a discussion of Gaussian process regression as far as I could see (the nearest point of approach is the use of Gaussian radial basis functions [oops: having written that, I immediately came across a brief discussion (S5.8.1) of, essentially, GP regression - though with no reference to standard literature]).
 
2 Star Rating  "Not recommended as a text book"2009-03-01
- Reviewed By User: A3PP2OYXEEEQO4
I had to use this book as the text book for a Machine Learning course at MIT and it was not very understantable. There are much better Machine Learning text books.
 
5 Star Rating  "Good Book!"2008-09-22
- Reviewed By User: A4X1CLCT2Y935
The book is really helpful and was being delivered to me in a timely fashion.
 
Quick Links



Last updated: Nov 21, 2009 at 18:59 EST. Pricing information is provided by the listed merchants. GoSale.com is not responsible for the accuracy of pricing information, product information or the images provided. Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on amazon.com or other merchants at the time of purchase will apply to the purchase of this product. As always, be sure to visit the merchant's site to review and verify product information, price, and shipping costs. GoSale.com is not responsible for the content and opinions contained in customer submitted reviews.
© 2009 GoSale.com (S2)



Home > Books > Computers & Internet > Certifications > By Subject > Visual C