This short interactive tutorial will show you how to use the scikit-learn Python package to perform basic machine learning analysis. It will also cover how to visualize your results with the matplotlib and seaborn Python packages.
You can access the code for this tutorial here.
|1. Preliminaries||Introduction to the tutorial and dataset|
|2. Core concepts||Estimators, regression, classification and clustering in scikit-learn|
|3. Pipelines||Transformers, preprocessing, feature selection, feature engineering, dimensionality reduction and pipelines in scikit-learn|
|4. Overfitting||The problem of overfitting, cross-validation, regularization and hyper-parameter tuning in scikit-learn|
|5. Visualization||Basic components of a matplotlib plot and basic plots with seaborn|