Introduction to Statistical Learning in Python

This contains my personal notes and solutions to exercises done in the scope of working through this book.

To get the files you can use

wget https://www.statlearning.com/s/ALL-CSV-FILES-2nd-Edition-corrected.zip

Introduction

These are my personal notes while working through the Introduction to Statistical Learning in Python Book

Exercise Progress

2. Statistical Learning 🌟🌟🌟🌟🌟🌟🌟 , 🌟🌟🌟

3. Linear Regression

Conceptual

1. ❌
2. ❌
3. ✅
4. ❌
5. ✅
6. ❌
7. ❌

Applied

8. ❌
9. ❌
10. ❌
11. ❌
12. ❌
13. ❌
14. ❌
15. ❌

4. Classification

Conceptual

1. ✅
2. ✅
3. ✅
4. ❌
5. ❌
6. ❌
7. ❌
8. ❌
9. ❌
10. ❌
11. ❌
12. ❌

Applied

13. ✅
14. ❌
    1. ✅
    2. ✅
    3. ✅
    4. ❌
    5. ❌
    6. ❌
    7. ❌
15. ✅
16. ❌

5. Resampling Methods

Conceptual ⭐⭐⭐⭐

Applied

5. ❌
6. ❌
7. ❌
8. ❌
9. ❌

5. Resampling Methods

Conceptual ⭐⭐⭐⭐

Applied

5. ❌
6. ❌
7. ❌
8. ❌
9. ❌

7. Moving Beyond Linearity

Conceptual

1. ✅
2. ❌
3. ❌
4. ❌
5. ❌

Applied

6. ❌
7. ❌
8. ❌
9. ❌
10. ❌
11. ❌
12. ❌

10. Deep Learning

Conceptual

1. ✅
2. ✅
3. ✅
4. ✅
5. ❌

Applied

6. ✅
7. ❌
8. ❌
9. ❌
10. ❌
11. ❌
12. ❌
13. ❌

Labs Progress

2. ✅

3. ✅

4. ✅

5. ❌

6. ❌

7. ✅

Technical Details

I've tried to get this working with Python3.12, but it doesn't seem to be compatible so I'll stick to python 3.11 for this repo.

References

• Book in Question
  • https://www.statlearning.com
• Original Repo of the notebooks
  • https://github.com/intro-stat-learning/ISLP_labs