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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
178 global ratings
5 star
82%
4 star
10%
3 star
3%
2 star
1%
1 star
4%
An Introduction to Statistical Learning: with Applications in R

An Introduction to Statistical Learning: with Applications in R

byGareth James
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178 total ratings, 15 with reviews

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From Canada

Lilly
4.0 out of 5 stars Great book, but I received a damaged copy
Reviewed in Canada ๐Ÿ‡จ๐Ÿ‡ฆ on March 14, 2022
Verified Purchase
This is a great book. I minus one star since I received a damaged copy. This book has a plastic wrap, hence it is less damaged than another book shipped in the same order.
One person found this helpful
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Frรฉdรฉric J.
5.0 out of 5 stars This is a question
Reviewed in Canada ๐Ÿ‡จ๐Ÿ‡ฆ on May 4, 2022
Another Amazon page showing this title in an edition from August 16 2021, tells us that this one here is the later edition, however it mentions that it's from July 30 2021... Which is incoherent. But where's the error, which one is the latest edition in the end?
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From other countries

Emma Peng
5.0 out of 5 stars Very helpful for non-statistic beginners, remember to learn it with their Videos!
Reviewed in Germany ๐Ÿ‡ฉ๐Ÿ‡ช on January 5, 2023
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The two professors in the video are the cutest old guy I have ever met!!!
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Arturo Sbr
5.0 out of 5 stars Greatest Data Science book ever (coming from someone who hates R)
Reviewed in Mexico ๐Ÿ‡ฒ๐Ÿ‡ฝ on October 12, 2022
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I reviewed this book for a class in my master's program and I loved it from start to end.
I already knew most of the concepts but became hooked because of how clear the explanations are. The authors convey complex ideas with remarkable simplicity, and for that, I think this is the most important book for data scientists.
I am an avid opposer of the R programming language (ew) and even I enjoyed the applied programming parts of the book.
In all honesty, the applications in R are very good, but it's not the main focus of the book. I think people should read this to understand the inner workings of the most popular AI algorithms instead of learning how to train predictive models (especially in R, haha).
Overall, I think this is a great book for beginners and veterans alike. I would not hesitate to recommend this book to anyone interested in statistics, data and AI.
2 people found this helpful
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Youngsuk L.
5.0 out of 5 stars very nice book
Reviewed in the United Kingdom ๐Ÿ‡ฌ๐Ÿ‡ง on June 23, 2022
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This is really a good book. Machine learning is a form of statistical learning and this book provides a great introduction.
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Terry
5.0 out of 5 stars If you know a little this will add a lot
Reviewed in the United Kingdom ๐Ÿ‡ฌ๐Ÿ‡ง on April 28, 2022
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If you know a little statistics and basics of using R / RStudio then this book will be very useful.
Bought it for a Masters course but provides a lot of background for business analytics as well
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Mary
5.0 out of 5 stars Best book on this subject
Reviewed in the United Kingdom ๐Ÿ‡ฌ๐Ÿ‡ง on May 15, 2022
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Honestly this book carried me through my statistics masters, it had the perfect detail for this course and covered many of my modules
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3.0 out of 5 stars ๅ•†ๅ“ใฎ็Šถๆ…‹ใŒ...
Reviewed in Japan ๐Ÿ‡ฏ๐Ÿ‡ต on November 3, 2022
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ใ‚ซใƒใƒผใฎไธ€้ƒจใŒ็ ดใ‘ใฆใ„ใพใ—ใŸ(ใƒใƒผใƒ‰ใ‚ซใƒใƒผใชใฎใซ...)
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Vaibhav gupta
5.0 out of 5 stars Nice book for learning statistical machine learning
Reviewed in the United States ๐Ÿ‡บ๐Ÿ‡ธ on September 24, 2022
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Good book for beginners who want to learn about machine learning
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Akimon85
5.0 out of 5 stars Excellent book
Reviewed in the United States ๐Ÿ‡บ๐Ÿ‡ธ on March 8, 2022
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I recently used this book along with a couple others in a graduate level ML course. IMO it was the best in terms of striking a good balance; containing enough detail to help grasp theory but not so much that it becomes a slog to get through. I used the Ebook in class and liked it enough to buy a hardcopy. Unfortunately, the print font size is quite small. Overall dimension is smaller than listed on Amazon. Maybe that was how big the 1st edition was?
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