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scikit-learn 1.3.2
Other versions

Please cite us if you use the software.

# External Resources, Videos and Talks

For written tutorials, see the Tutorial section of the documentation.

## New to Scientific Python?

For those that are still new to the scientific Python ecosystem, we highly recommend the Python Scientific Lecture Notes. This will help you find your footing a bit and will definitely improve your scikit-learn experience. A basic understanding of NumPy arrays is recommended to make the most of scikit-learn.

## External Tutorials

There are several online tutorials available which are geared toward specific subject areas:

- Machine Learning for NeuroImaging in Python

- Machine Learning for Astronomical Data Analysis

## Videos

- An introduction to scikit-learn Part I and Part II at Scipy 2013 by Gael Varoquaux, Jake Vanderplas and Olivier Grisel. Notebooks on github.

- Introduction to scikit-learn by Gael Varoquaux at ICML 2010

  > A three minute video from a very early stage of scikit-learn, explaining the basic idea and approach we are following.

- Introduction to statistical learning with scikit-learn by Gael Varoquaux at SciPy 2011

  > An extensive tutorial, consisting of four sessions of one hour. The tutorial covers the basics of machine learning, many algorithms and how to apply them using scikit-learn. The material corresponding is now in the scikit-learn documentation section A tutorial on statistical-learning for scientific data processing.

- Statistical Learning for Text Classification with scikit-learn and NLTK (and slides) by Olivier Grisel at PyCon 2011

  > Thirty minute introduction to text classification. Explains how to use NLTK and scikit-learn to solve real-world text classification tasks and compares against cloud-based solutions.

- Introduction to Interactive Predictive Analytics in Python with scikit-learn by Olivier Grisel at PyCon 2012

  > 3-hours long introduction to prediction tasks using scikit-learn.

- scikit-learn - Machine Learning in Python by Jake Vanderplas at the 2012 PyData workshop at Google

  > Interactive demonstration of some scikit-learn features. 75 minutes.

- scikit-learn tutorial by Jake Vanderplas at PyData NYC 2012

  > Presentation using the online tutorial, 45 minutes.