shilpa9a/Introduction_to_statistical_learning_summary_python
Summary of each chapter of the book- Introduction of Statistical Learning (ISL), along with Python code & data.
This project helps data analysts and scientists quickly grasp core statistical machine learning concepts by providing a concise summary of the "Introduction to Statistical Learning" book. It translates complex statistical methods into practical Python code, allowing users to apply them to their own datasets. You get explained statistical learning techniques alongside Python code and sample data, enabling hands-on learning for building and testing models.
188 stars. No commits in the last 6 months.
Use this if you want to quickly learn or refresh your understanding of fundamental statistical machine learning concepts and their implementation in Python, especially if you have a non-technical background.
Not ideal if you need to learn about time series models, neural networks, deep learning, or Bayesian methods, as these topics are not covered.
Stars
188
Forks
86
Language
Jupyter Notebook
License
—
Category
Last pushed
Jul 23, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/shilpa9a/Introduction_to_statistical_learning_summary_python"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
harvard-edge/cs249r_book
Machine Learning Systems
wx-chevalier/AI-Notes
:books: [.md & .ipynb] Series of Artificial Intelligence & Deep Learning, including Mathematics...
datawhalechina/key-book
《机器学习理论导引》（宝箱书）的证明、案例、概念补充与参考文献讲解。
rickiepark/handson-ml3
<핸즈온 머신러닝 3판>의 주피터 노트북 저장소
Ceyron/machine-learning-and-simulation
All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine...