Tools / Data science and machine learning libraries
scikit-learn
Python's standard library for classic machine learning. Models, preprocessing, pipelines and evaluation.
About 15 hours of study. It builds on Data wrangling with pandas.
Where to learn it
The scikit-learn developers
Getting Started, then the User Guide sections you need
Kaggle
Intro to Machine Learning, then Intermediate Machine Learning
Short hands-on courses that run in the browser.
Wrong chapter, dead link, or know something better? Tell us on GitHub.
Your route to scikit-learn
Pick where you’re starting from. Anything your background already covers is left out, and the rest is put in order.
3 stops to go, about 80 hours of study.
Open a stop to see the book, the video course and the practice for it. Tick its circle when you've finished.
- 40 h
Programming. Ready to start.
- Tool25 h
Data. After Programming in Python.
- Tool15 h
Machine learning. After Data wrangling with pandas.
That's the whole route to scikit-learn.
What it needs and what it leads to: scikit-learn on the map.