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 5+ Years Experience
- JavaScript Interview Questions for 2–5 Years Experience
- JavaScript Interview Questions for 1–2 Years Experience
- 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
Tutorials
Follow us on Linkedin
Random Blogs
- Datasets for Speech Recognition Analysis
- Data Analytics: The Power of Data-Driven Decision Making
- Top 15 Recommended SEO Tools
- Compiler SQL Online: A Beginner-Friendly Guide to Running SQL Queries Anywhere
- Internet of Things (IoT) & AI – Smart Devices and AI Working Together
- Understanding OLTP vs OLAP Databases: How SQL Handles Query Optimization
- The Ultimate Guide to Data Science: Everything You Need to Know
- SQL Joins Explained: A Complete Guide with Examples
- Understanding LLMs (Large Language Models): The Ultimate Guide for 2025
- Role of Digital Marketing Services to Uplift Online business of Company and Beat Its Competitors
- Variable Assignment in Python
- Python Challenging Programming Exercises Part 3
- Datasets for analyze in Tableau
- Types of Numbers in Python
- Google’s Core Update in May 2020: What You Need to Know
- Avoiding the Beginner’s Trap: Key Python Fundamentals You Shouldn't Skip
Datasets for Machine Learning
- Awesome-ChatGPT-Prompts
- 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










