PyData Seattle 2015 Scikit-Learn Tutorial

This is the main index of the PyData Seattle 2015 Introduction to Scikit-Learn tutorial, presented by Jake VanderPlas. Please refer to the github repository for this tutorial for any updates.

Tutorial Notebooks

The following links are to notebooks containing the tutorial materials. Note that many of these require files that are in the directory structure of the github repository in which they are contained. There is not time during the tutorial to cover all of this material, but I left it in in case attendees would like to go deeper on their own.

1. Preliminaries

• 01-Preliminaries.ipynb

2. Introduction to Machine Learning with Scikit-Learn

• 02.1-Machine-Learning-Intro.ipynb
• 02.2-Basic-Principles.ipynb

3. Supervised Learning In-Depth

• 03.1-Classification-SVMs.ipynb
• 03.2-Regression-Forests.ipynb

4. Unsupervised Learning In-Depth

• 04.1-Dimensionality-PCA.ipynb
• 04.2-Clustering-KMeans.ipynb
• 04.3-Density-GMM.ipynb

5. Model Validation In-Depth

• 05-Validation.ipynb