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

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 ...

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

Any functions that accept a NumPy array as an argument should be properly typed, so that Cython knows how to interpret the argument as a NumPy array (fast) rather than a generic Python object (slow).

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.

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.

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