scipy_2016_notes
Tutorials
- [Software Carpentry Scientific Python Course (Beginner)](https://github.com/katyhuff/2016-07-11-scipy)
- [Network Science and Statistics: Fundamentals and Applications (Intermediate)](https://github.com/ericmjl/Network-Analysis-Made-Simple) - [Deep Learning for Image Recognition (Beginner)](https://github.com/rouseguy/scipyUS2016_dl-image) - [NumPy (Beginner)](https://github.com/enthought/Numpy-Tutorial-SciPyConf-2016) - [Symbolic Compution with Python using SymPy (Beginner)](https://github.com/sympy/scipy-2016-tutorial) - [Bokeh for Data Applications and Visualization (Intermediate)](https://github.com/bokeh/bokeh-notebooks) - [Simulating Robot, Vehicle, Spacecraft, and Animal Motion with Python (Advanced)] - [Data Science is Software: Developer #lifehacks for the Python Data Scientist (Intermediate)](https://github.com/pjbull/data-science-is-software) - [Numba: Tell those C++ bullies to get lost (Intermediate)](https://github.com/barbagroup/numba_tutorial_scipy2016)
- [Time Series Analysis with Python (Intermediate)](https://github.com/AileenNielsen/TimeSeriesAnalysisWithPython) - [Machine Learning with scikit-learn (Intermediate)](https://github.com/amueller/scipy-2016-sklearn) - [Matplotlib Tutorial (Beginner)](https://github.com/rougier/matplotlib-tutorial) - [Parallel Python: Analyzing Large Datasets (Intermediate)](https://github.com/mrocklin/scipy-2016-parallel) - The Google compute clusters used during the workshop may not work in the future. - [Scikit-image: Image analysis in Python (Intermediate)] - [Analyzing and Manipulating Data with Pandas (Beginner)](https://github.com/jonathanrocher/pandas_tutorial) - [Scalable Hierarchical Parallel Computing (Intermediate)](https://github.com/mmckerns/tuthpc) - [Geographic Data Science with PySAL and the pydata stack (Beginner)](https://github.com/darribas/gds_scipy16)