Optimizing Numerical Calculations in Python

Optimizing Numerical Calculations in Python
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.

Data Visualization with Python and Matplotlib ☞ http://bit.ly/2U3Jijg
Data Analysis with Python & Pandas ☞ http://bit.ly/2ULzTS5
Neural Networks Fundamentals in Python ☞ http://bit.ly/2Kgf4dh

Social Network for Developers ☞ https://morioh.com
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Learn to code for free and get a developer job ☞ https://codequs.com/


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