An Introduction to Statistical Learning
With Applications in R
Recommended by Roger D. Peng, and 1 others. See all reviewsRanked #2 in Data Science, Ranked #3 in Data Mining — see more rankings.
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and... more
Reviews and Recommendations
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Roger D. Peng This book is written by a powerhouse of authors in the machine learning community, true authorities in the field. But beyond that, they’re also great writers. (Source)
Rankings by Category
An Introduction to Statistical Learning is ranked in the following categories:
- #30 in Artificial Intelligence
- #22 in Big Data
- #54 in Computer Science
- #8 in Deep Learning
- #3 in Machine Learning
- #7 in Mathematical Physics
- #14 in Probability
- #67 in Software Engineering
- #11 in Statistics
- #38 in Technical
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