An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
Product ID: 1594976
🎨Vivid color graphics & real-world examples
📈Hands-on R tutorials in every chapter
📊Covers 10+ key modeling techniques
€ 77.94
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Description
📚 Unlock the data science edge every manager needs!
- VISUAL LEARNING BOOST - Colorful graphics clarify complex concepts for intuitive understanding.
- CODE READY WITH R LABS - Practical R tutorials empower immediate data science application.
- BROAD INDUSTRY RELEVANCE - Ideal for data-driven decision makers in finance, marketing, biology & beyond.
- ACCESSIBLE YET AUTHORITATIVE - Written by top statisticians, perfect for managers & practitioners alike.
- MASTER CORE STATISTICAL LEARNING - From linear regression to SVM, unlock essential predictive tools.
An Introduction to Statistical Learning is a bestselling, accessible textbook that demystifies key statistical learning methods with practical R code and vivid examples. Authored by leading statisticians, it equips professionals and aspiring data scientists with essential tools to analyze complex data across industries, blending theory with hands-on application.
Specifications
| Best Sellers Rank | #679,433 in Books ( See Top 100 in Books ) #157 in Probability & Statistics (Books) #555 in Statistics (Books) |
| Customer Reviews | 4.8 4.8 out of 5 stars (1,933) |
| Dimensions | 6.1 x 1 x 9.3 inches |
| Edition | 1st |
| ISBN-10 | 1461471370 |
| ISBN-13 | 978-1461471370 |
| Item Weight | 2.31 pounds |
| Language | English |
| Part of series | Springer Texts in Statistics |
| Print length | 426 pages |
| Publication date | January 1, 2013 |
| Publisher | SPRINGER |
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