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This tutorial is geared towards data scientists and Python users looking to take their Python performance to the next level.
Cython is a foundational technology behind many packages you use everyday, including NumPy, SciPy, Pandas, Scikit-Learn, Scikit-Image, PyTables, and h5py. Developers, data scientists, and researchers use Cython to accelerate Python, access NumPy efficiently at the C level, and interface Python with C or C++. Cython's expressivity, its stability and maturity, and its gradual typing approach make it a uniquely flexible tool that has become a critical component for many projects. This tutorial will be fast paced, and is geared towards data scientists and Python users looking to take their Python performance to the next level. Basic familiarity with C or C++ is assumed.
Tutorial materials found here: https://scipy2017.scipy.org/ehome/220...