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Course outline: "Master Machine Learning with scikit-learn"
Course overview: "Master Machine Learning with scikit-learn"
Introduction to model ensembling
How to save a scikit-learn Pipeline with custom transformers
Should I shuffle samples with cross-validation?
Cost-sensitive learning in scikit-learn
scikit-learn vs Deep Learning
How to read the scikit-learn documentation
My top 50 scikit-learn tips
21 more pandas tricks
Adapt this pattern to solve many Machine Learning problems
Tune multiple models simultaneously with GridSearchCV
Access part of a Pipeline using slicing
Tune the parameters of a VotingClassifer or VotingRegressor
Ensemble multiple models using VotingClassifer or VotingRegressor
Create feature interactions using PolynomialFeatures
Speed up GridSearchCV using parallel processing
Use OrdinalEncoder instead of OneHotEncoder with tree-based models
Passthrough some columns and drop others in a ColumnTransformer
Drop the first category from binary features (only) with OneHotEncoder
Estimators only print parameters that have been changed
Load a toy dataset into a DataFrame
Get the feature names output by a ColumnTransformer
Create an interactive diagram of a Pipeline in Jupyter