This tutorial will offer an in-depth experience of methods and tools for the Machine Learning practitioner through a selection of advanced features of scikit-learn and related projects. This tutorial targets developers already familiar with machine learning concepts and scikit-learn who wish to learn how to apply those tools on larger datasets using multicore machines or distributed clusters.
Scikit-learn is an actively developing python package providing implementations of many of the most popular and powerful machine learning methods used today.
Recently the popularity of scikit-learn was emphasized by its use by top contestants on machine learning challenges hosted by kaggle.
The goal of this tutorial is to share some recipes to fully leverage the library for predictive modeling. In particular we will cover the following points:
Update: See updated tutorial preparation instructions at Advanced Machine Learning with scikit-learn