An Introduction to Statistical Learning with Applications in R

Book Details
Author | Gareth James • Daniela Witten • Trevor Hastie Robert Tibshirani |
---|---|
Publisher | Springer |
Published Year | 1905 |
Pages | 440 |
Language | English |
ISBN-10 | 1071614177 |
ISBN-13 | 978-1071614174 |
An Introduction to Statistical Learning with Applications in R is a widely acclaimed textbook by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani. It provides a clear and accessible introduction to statistical and machine learning techniques, with a strong focus on practical applications using the R programming language. The book covers key topics such as linear regression, classification, resampling methods, model selection, and more, making it ideal for beginners and practitioners in data science and statistics.

Prepare for Interview
- JavaScript Interview Questions for 0–1 Year Experience
- JavaScript Interview Questions For Fresher
- SQL Interview Questions for 5+ Years Experience
- SQL Interview Questions for 2–5 Years Experience
- SQL Interview Questions for 1–2 Years Experience
- SQL Interview Questions for 0–1 Year Experience
- SQL Interview Questions for Freshers
- Design Patterns in Python
- Dynamic Programming and Recursion in Python
- Trees and Graphs in Python
- Linked Lists, Stacks, and Queues in Python
- Sorting and Searching in Python
- Debugging in Python
- Unit Testing in Python
- Asynchronous Programming in PYthon
- Multithreading and Multiprocessing in Python
- Context Managers in Python
- Decorators in Python
Tutorials
Follow us on Linkedin
Random Blogs
- Internet of Things (IoT) & AI – Smart Devices and AI Working Together
- Python Challenging Programming Exercises Part 2
- Python Challenging Programming Exercises Part 3
- AI in Marketing & Advertising: The Future of AI-Driven Strategies
- The Ultimate Guide to Data Science: Everything You Need to Know
- Convert RBG Image to Gray Scale Image Using CV2
- Government Datasets from 50 Countries for Machine Learning Training
- The Beginner’s Guide to Normalization and Denormalization in Databases
- Avoiding the Beginner’s Trap: Key Python Fundamentals You Shouldn't Skip
- Generative AI - The Future of Artificial Intelligence
- Mastering SQL in 2025: A Complete Roadmap for Beginners
- String Operations in Python
- AI in Cybersecurity: The Future of Digital Protection
- Quantum AI – The Future of AI Powered by Quantum Computing
- SQL Joins Explained: A Complete Guide with Examples
- How AI Companies Are Making Humans Fools and Exploiting Their Data
Datasets for Machine Learning
- Amazon Product Reviews Dataset
- Ozone Level Detection Dataset
- Bank Transaction Fraud Detection
- YouTube Trending Video Dataset (updated daily)
- Covid-19 Case Surveillance Public Use Dataset
- US Election 2020
- Forest Fires Dataset
- Mobile Robots Dataset
- Safety Helmet Detection
- All Space Missions from 1957
- OSIC Pulmonary Fibrosis Progression Dataset
- Wine Quality Dataset
- Google Audio Dataset
- Iris flower dataset
- Artificial Characters Dataset