scikit-learn：External Resources, Videos and Talks

参考：http://scikit-learn.org/stable/presentations.html

scikit-learn的User Guide基本看完了（除了具体estimator部分），这里再摘录scikit-learn官方网站提供的额外资源，供之后学习。

关于supervised learning和unsupervised learning中涉及到的estimator，用到的时候再看吧，之后也会陆续更新，不过不会像之前这段时间这么集中的去更新了。

感谢这段时间大家的支持。。。

祝大家学习进步，工作顺利。

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 the scikit, 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.

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