We’ve seen SciPy in some Hackaday contest entries before. You can think of it like Matlab for Python . Just keep in mind, it isn’t an inherent part of Python.

Continuum Analytics is pleased to announce a technical collaboration with Intel resulting in the Intel® Distribution for Python powered by Anaconda.

Intel Distribution for Python adds Intel's high-speed math libraries to the existing, highly convenient Anaconda version for data scientists Topics Spotlight: Advancing IT Leadership ...

David Bolton from Slashdot shows how ‘embarrassingly parallel’ code can be sped up over 2000x (not percent) by utilizing Intel tools including the Intel Python compiler and OpenMP. "The Intel ...

Still, Numba is one of the best approaches to exploiting parallelism, and anyone developing scientific computing software in Python should become aware of its capabilities. Intel Distribution for ...

You’d have to build the NumPy and SciPy libraries to use Intel MKL all on your own. Enthought Canopy. The Enthought Canopy distribution of Python resembles Anaconda in many ways.

The momentum behind the language is driven by useful libraries that get developed, he adds. These include the NumPy and SciPy libraries for Python, which Netflix uses to perform numerical analysis ...

“Python is a very easy language to learn for non-programmers,” said Peter Wang, president of Continuum Analytics. That’s important because most big-data analysts will probably not be ...