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An Introduction to Statistical Learning: with Applications in R (Springer Te...

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Item specifics

Condition
Like New: A book that looks new but has been read. Cover has no visible wear, and the dust jacket ...
Release Year
2013
Book Title
An Introduction to Statistical Learning: with Applications in ...
Subject
Mathematical & Statistical Software, Probability & Statistics / General, Intelligence (Ai) & Semantics
ISBN
9781461471370
Subject Area
Computers, Mathematics
Publication Name
Introduction to Statistical Learning : with Applications in R
Item Length
9.5 in
Publisher
Springer New York
Series
Springer Texts in Statistics Ser.
Publication Year
2017
Type
Textbook
Format
Hardcover
Language
English
Item Height
0.9 in
Author
Trevor Hastie, Gareth James, Robert Tibshirani, Daniela Witten
Item Width
6.4 in
Item Weight
35.8 Oz
Number of Pages
Xiv, 426 Pages

About this product

Product Identifiers

Publisher
Springer New York
ISBN-10
1461471370
ISBN-13
9781461471370
eBay Product ID (ePID)
159944459

Product Key Features

Author
Trevor Hastie, Gareth James, Robert Tibshirani, Daniela Witten
Publication Name
Introduction to Statistical Learning : with Applications in R
Format
Hardcover
Language
English
Subject
Mathematical & Statistical Software, Probability & Statistics / General, Intelligence (Ai) & Semantics
Series
Springer Texts in Statistics Ser.
Publication Year
2017
Type
Textbook
Subject Area
Computers, Mathematics
Number of Pages
Xiv, 426 Pages

Dimensions

Item Length
9.5 in
Item Height
0.9 in
Item Width
6.4 in
Item Weight
35.8 Oz

Additional Product Features

Intended Audience
Scholarly & Professional
Series Volume Number
103
Number of Volumes
1 Vol.
Lc Classification Number
Qa276-280
Copyright Date
2013
Dewey Decimal
519.5
Dewey Edition
23
Illustrated
Yes

Item description from the seller

mfts9556

mfts9556

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5.0
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Most relevant reviews

  • One of the best introductory books on machine learning

    This is one of the best introductory books on machine learning, including regression, classification, resampling, clustering, support vector machines and tree-based methods.

    Verified purchase: YesCondition: NewSold by: maylasc_0

  • A great onramp to Stats and Machine Learning

    I got turned onto the ISLR by DataRobot support personnel who said it described the theoretical underpinning of the models DataRobot vets/uses. I found it readable, approachable and far better organized than the materials of various MOOCs I took which covered the same material. I have a far better grasp of the material now than I did before reading.

    Verified purchase: YesCondition: NewSold by: expres_94

  • Comprehensive and technical enough

    I am learning data science and i have finished the first three chapters of this book. It is easier to understand than some more technical books that people read in their PhD programs. At the same time it went deeper than Coursera courses and some o’Reilly books I read

    Verified purchase: YesCondition: NewSold by: crestview-stor

  • great intro book to the topic

    excellent intro book, well written and easy to read through if you have undergrad math/eng knowledge

    Verified purchase: YesCondition: NewSold by: crestview-stor

  • Good new book

    What else can I say. Arrived timely

    Verified purchase: YesCondition: NewSold by: expres_94