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

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.

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

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.

NumPy is known for being fast, but could it go even faster? Here’s how to use Cython to accelerate array iterations in NumPy. NumPy gives Python users a wickedly fast library for working with ...

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

[Zoltán] sends in his very interesting implementation of a NumPy-like library for micropython called ulab. He had a project in MicroPython that needed a very fast FFT on a micro controller, and ...

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 ...

As part of the Python Tools for Visual Studio project the well-known NumPy and SciPy libraries were ported to .NET. The port, which combines C# and C interfaces over a native C core, was done in ...

Learn about some of the best Python libraries for programming Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL).