Mathew K AnalyticsScikit-learn deep dive
A free 18-lesson course. Every lesson has a video walkthrough and a Jupyter notebook you can download or open in Google Colab. Tools covered: scikit-learn, NumPy, pandas, SciPy.
17 minLesson 1
Scikit-learn Tutorial #1: The Estimator API Explained
17 minLesson 2
Scikit-learn Tutorial #2: Preprocessing — Scalers
16 minLesson 3
Scikit-learn Tutorial #3: Preprocessing — Encoders
15 minLesson 4
Scikit-learn Tutorial #4: Handling Missing Data
16 minLesson 5
Scikit-learn Tutorial #5: Feature Engineering
15 minLesson 6
Scikit-learn Tutorial #6: Pipelines
15 minLesson 7
Scikit-learn Tutorial #7: ColumnTransformer
15 minLesson 8
Scikit-learn Tutorial #8: Splitting & Cross-Validation
15 minLesson 9
Scikit-learn Tutorial #9: Hyperparameter Tuning
15 minLesson 10
Scikit-learn Tutorial #10: Classification Metrics
14 minLesson 11
Scikit-learn Tutorial #11: Regression Metrics
14 minLesson 12
Scikit-learn Tutorial #12: Clustering Metrics
14 minLesson 13
Scikit-learn Tutorial #13: Feature Selection
14 minLesson 14
Scikit-learn Tutorial #14: Text Data & Vectorisation
14 minLesson 15
Scikit-learn Tutorial #15: Ensembling & Meta-Estimators
15 minLesson 16
Scikit-learn Tutorial #16: Custom Estimators
15 minLesson 17
Scikit-learn Tutorial #17: Model Persistence & Diagnostics
16 minLesson 18