In this article, we’ll introduce you to some of the libraries that have helped make Python the most popular language for data science in Stack Overflow’s 2016 developer poll.

Python can be made faster by way of external libraries, third-party JIT compilers (PyPy), and optimizations with tools like Cython, but Julia is designed to be faster right out of the gate.

But data science is a specific field, so while Python is emerging as the most popular language in the world, R still has its place and has advantages for those doing data analysis.

But Continuum Analytics in Austin, Texas, have released Anaconda, a free package that bundles together around 200 of the most popular Python libraries for science, maths, engineering and data ...

Nvidia wants to extend the success of the GPU beyond graphics and deep learning to the full data science experience. Open source Python library Dask is the key to this.

This article rounds up some of the most valuable free data science courses offered by top institutions like Harvard, IBM, and ...

Python is the most popular programming language, outranking C and C++. Enterprises are using Python for HPC with the help of Intel Performance Libraries.

What are some use cases for which it would be beneficial to use Haskell, rather than R or Python, in data science? This question was originally answered on Quora by Tikhon Jelvis.