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  • An Introduction to Statistical Learning: with Applications in R...
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Customer reviews

4.7 out of 5 stars
4.7 out of 5
1,812 global ratings
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4 star
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An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

bygareth-james
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Guillermo Martinez Dibene
5.0 out of 5 starsGreat introductory survey to many statistical tools and R code
Reviewed in Canada 🇨🇦 on February 1, 2022
This book is quite fantastic for an introductory level. I have a specialised training in mathematics and this books puts me up to date on several topics and algorithms without having to deal much time in the mathematical technicalities (for that, there are specialised treatises on each subject). The R code is quite good and although I think some of their advice is not appropriate (e.g. the attach function is in R only for legacy purposes but shouldn't be used since it overrides other functions, including base, aka default, functions), it is workable and so it's a great investment. The book is introductory focusing mostly on intuition and how to do, little time is spent in mathematical formalities, so that's a plus. I think there is a NEWER edition than the one I reviewed but otherwise I suspect the newer edition will be just better. Recommended.
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Sandeep Sony
3.0 out of 5 starsOld edition
Reviewed in Canada 🇨🇦 on November 3, 2020
I bought this as a used book, however, the book was an old edition and had errors, so returned it.
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From Canada

Guillermo Martinez Dibene
5.0 out of 5 stars Great introductory survey to many statistical tools and R code
Reviewed in Canada 🇨🇦 on February 1, 2022
Verified Purchase
This book is quite fantastic for an introductory level. I have a specialised training in mathematics and this books puts me up to date on several topics and algorithms without having to deal much time in the mathematical technicalities (for that, there are specialised treatises on each subject). The R code is quite good and although I think some of their advice is not appropriate (e.g. the attach function is in R only for legacy purposes but shouldn't be used since it overrides other functions, including base, aka default, functions), it is workable and so it's a great investment. The book is introductory focusing mostly on intuition and how to do, little time is spent in mathematical formalities, so that's a plus. I think there is a NEWER edition than the one I reviewed but otherwise I suspect the newer edition will be just better. Recommended.
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jay han
5.0 out of 5 stars nearly new
Reviewed in Canada 🇨🇦 on March 31, 2022
Verified Purchase
great condition, like new. Looks like someone opened it once and never again. no complaints
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Demetri Pananos
4.0 out of 5 stars Good introduction, but the book lacks details.
Reviewed in Canada 🇨🇦 on July 5, 2016
Verified Purchase
This book is a gentle introduction to the realm of statistical learning. Aimed at practitioners of disciplines other than mathematics, the book gives an overview of learning and estimation methods for a wide variety of problems.

However, I struggle to see who in actuality would benefit from this book. The topics are not so easy to understand that just anyone can read the book. Topics require knowledge of linear algebra, probability theory, multivariable calculus, and an intimate knowledge of statistical methods. So, if readers are to be familiar with these topics, why forgo matrix notation in the chapters for multiple regression? Why omit various proofs of equalities? Why feel the need to "dumb down" the book?

In summation, the book would serve people familiar with mathematics well if they seek to familiarize themselves with various statistical learning procedures (like cross validation, boot strapping, and regularization). Curious readers will need seek more thorough explanations of the concepts elsewhere.
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Chris Czerwinski
4.0 out of 5 stars Great examples with R coding
Reviewed in Canada 🇨🇦 on November 9, 2020
Verified Purchase
I loved the R coding especially to newcomers learning Statistics. What would have even been better is an Appendix on how to setup a small data base of a matrix or table of 10 by 5 elements using R.
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Madhuran Thiagarajah
5.0 out of 5 stars very good. Seriously
Reviewed in Canada 🇨🇦 on August 9, 2017
Verified Purchase
Shiny cover, no scratches, crisp pages... very good.

Seriously, this is a good introduction to machine learning. I'm starting to go through this cover to cover and I'm finding the book very accessible. My background: Biology major with only basic familiarity with statistics, and linear algebra (intro level university courses), and have dabbled a fair bit with programing and basic machine learning in the past. The authors provide just enough basic math, and notation to be able to understand it, and coupled with the video lectures you can find online you will get a very good intuitive understanding of some of the most common machine learning methods. For those who prefer python, someone adapted the exercises for python and made it freely available which can be found easily with a quick search.
4 people found this helpful
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Amazon Customer
5.0 out of 5 stars Fast shipping
Reviewed in Canada 🇨🇦 on March 5, 2021
Verified Purchase
Fast shipping and inside of the book is pretty new
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Johan
5.0 out of 5 stars Excellent !
Reviewed in Canada 🇨🇦 on September 17, 2020
Verified Purchase
Received today! At least 3 days ahead of schedule. The book is in excellent condition and just like brand new. Rally happy with my purchase !
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Johan
5.0 out of 5 stars Excellent !
Reviewed in Canada 🇨🇦 on September 17, 2020
Received today! At least 3 days ahead of schedule. The book is in excellent condition and just like brand new. Rally happy with my purchase !
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Amazon Customer
5.0 out of 5 stars Really good and accessible
Reviewed in Canada 🇨🇦 on February 13, 2020
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Really good and accessible for whoever already has elementary basics in statistics, the authors make sure to use concrete evidences and give you access to everything you need for the exercices on their website for no additionnal charges.
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Summer11
5.0 out of 5 stars Clear and concise textbook
Reviewed in Canada 🇨🇦 on March 23, 2021
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Good read!
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Sandeep Sony
3.0 out of 5 stars Old edition
Reviewed in Canada 🇨🇦 on November 3, 2020
Verified Purchase
I bought this as a used book, however, the book was an old edition and had errors, so returned it.
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