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The Best statistical learning with r of 2023 – Reviewed and Top Rated
After hours researching and comparing all models on the market, we find out the Best statistical learning with r of 2023. Check our ranking below.
2,356 Reviews Scanned
- James, Gareth (Author)
- English (Publication Language)
- 622 Pages - 07/30/2022 (Publication Date) - Springer (Publisher)
- This book presents some of the most important modeling and prediction techniques, along with relevant applications
- Topics include linear regression, classification, re-sampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented.
- Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform
- Hardcover Book
- James, Gareth (Author)
- Language Published: English
- Binding: Hardcover
- Comes in Good condition
- Hardcover Book
- Hastie, Trevor (Author)
- Gutierrez, Daniel D. (Author)
- English (Publication Language)
- 282 Pages - 09/18/2015 (Publication Date) - Technics Publications (Publisher)
- Hardcover Book
- Ott, R. (Author)
- English (Publication Language)
- 1296 Pages - 06/11/2015 (Publication Date) - Cengage Learning (Publisher)
Last update on 2025-07-03 / Affiliate links / Product Titles, Images, Descriptions from Amazon Product Advertising API
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FAQ:
Q: Is your programming worth learning?
A: Persistence and Patience are the key to beginning data science with R programming language, but considering the wonders R language can do, it is worth learning R language now. R language has a teaching package called Swirl that helps beginners learn commands and also provides immediate user feedback.
Q: What is introduction in statistics?
A: Introductory Statistics is designed for a one- or two-semester first course in applied statistics and is intended for students who do not have a strong background in mathematics. This course makes the subject of statistics interesting and accessible to a wide and varied audience by providing realistic content in examples.
Q: What is your in statistics?
A: R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis.
Q: What is your in data science?
A: R is data analysis software: Data scientists, statisticians, and analysts—anyone who needs to make sense of data, really—can use R for statistical analysis, data visualization, and predictive modeling. R is a programming language: An object-oriented language created by statisticians, R provides objects, operators,…
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