ISLR-python and ISL-python

The Python code for the "An Introduction to Statistical Learning" textbook (A) is complemented by solutions to its labs and exercises provided as Jupyter Notebooks (B).

ISLR-python
51
Established
ISL-python
51
Established
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Stars: 4,391
Forks: 2,406
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 349
Forks: 126
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About ISLR-python

JWarmenhoven/ISLR-python

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

This project provides Python code examples that replicate the statistical learning methods demonstrated in the 'An Introduction to Statistical Learning' textbook. It takes raw datasets and applies various machine learning techniques, showing the steps and resulting models. Anyone learning or teaching statistical modeling and machine learning concepts will find these examples useful.

statistical-modeling machine-learning-education data-analysis-training predictive-analytics academic-research

About ISL-python

a-martyn/ISL-python

Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.

This resource provides practical Python-based solutions for understanding and applying core statistical learning concepts from the textbook "An Introduction to Statistical Learning." It takes the theoretical exercises and labs from the book and translates them into executable Python code, complete with necessary datasets. It's designed for students or practitioners looking to deepen their grasp of statistical modeling.

statistical-modeling data-analysis-education machine-learning-fundamentals predictive-analytics model-interpretation

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