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

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.

[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 ...

JetBrains has detailed its eighth annual Python Developers Survey. This survey is conducted as a collaborative effort between the Python Software Foundation and JetBrains’ PyCharm team.