External Resources, Videos and Talks¶

For written documentation, see the user guide.

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 sklearn-theano experience. A basic understanding of NumPy arrays is recommended to make the most of scikit-learn.

A decent grasp of Theano is also useful for developers who wish to build their own modules or contribute.

Videos¶

Neural Networks for Computer Vision by Kyle Kastner at EuroScipy2014

A thirty minute talk describing the use of Python tools for computer vision, and introducing some of the core examples and usage of sklearn-theano.