PyData and SciPy Tutorials
==========================

Tutorials
---------

-  `Pandas <https://mybinder.org/v2/gh/deniederhut/Pandas-Tutorial-ScipyConf-2018/master>`_
-  `Scikit-Learn <https://mybinder.org/v2/gh/amueller/scipy-2018-sklearn/master>`_
-  `Scikit-image <https://mybinder.org/v2/gh/scikit-image/skimage-tutorials/master>`_
-  `Network analysis made simple <https://mybinder.org/v2/gh/ericmjl/Network-Analysis-Made-Simple/master>`_
-  `Bayesian Data Science Two Ways: Simulation and Probabilistic Programming <https://mybinder.org/v2/gh/ericmjl/bayesian-stats-modelling-tutorial/master>`_


Motivation
----------

This repository holds pointers to executable tutorials in the Python data
science ecosystem (Numpy, Pandas, Scikit-Learn, etc..).  It uses the following
resources:

1.  Existing tutorial materials from conferences
2.  Links to existing videos from conferences
3.  The public MyBinder deployment to quickly launch executable notebooks

The goal is to provide a central place where users that are new to the
ecosystem can quickly find and leverage existing educational material that the
community produces within technical conferences.


How to contribute
-----------------

1.  Find tutorials with notebooks that can be easily run from within a Binder
    environment.  These typically have the following attributes:
    -   They can run easily without much setup
    -   They include an environment.yaml or requirements.txt file that is sufficient for Binder to form a complete environment
    -   They can run quickly and safely in around 2GB of memory
    -   They are decently educational and are about tools and topics of broad interest
2.  Find videos of tutorial presenters delivering those tutorials
3.  Embed the videos within each notebook, starting at the time when that
    notebook is first discussed
4.  Engage in general planning of this repository, currently at
    https://github.com/mrocklin/tutorials