Libraries are collections of shared code. They're common in Python, where they're also called "modules," but they're also ...

NumPy, the Python package for scientific computing, is an adolescent with prospects for a prolific maturity.

Want to get better performance with Python? Here's how to use NumPy to toe the 'invisible line' of data and memory transfers and optimize efficiency.

Learn how this popular Python library accelerates math at scale, especially when paired with tools like Cython and Numba.

With Python and NumPy getting lots of exposure lately, I'll show how to use those tools to build a simple feed-forward neural network.

The Python extension for mathematical calculations is accelerated in version 2.0.0 with hardware support and offers many new functions.

Data scientist Dr. James McCaffrey begins a series on presenting and explaining the most common modern techniques used for neural networks, for which over the past couple of years there have been many ...

Resource loading optimization is the first step in improving frontend performance, and the Python backend plays a key role as the "resource scheduler". For static resources (CSS, JS, images), ...

There are many ways to boost Python application performance. Here are 10 hard-core coding tips for faster Python.