Optimizing Numerical Calculations in Python

  • 2019-04-18 03:28 AM
  • 412

Jakub Urban, a senior Pythonista from Quantlane with rich experience in scientific computing and modelling, will show various possibilities for making your (mostly) numerical calculations in Python fast.

He will cover optimization and parallelization using Numpy, Numba, Cython or Dask. You will learn that Python can be as fast as Fortran with a very little effort. In case it cannot, you will see how to seamlessly turn Fortran/C/C++ into a Python module.

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