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.

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

[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 ...

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.

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 ...

This course is a great way to go from zero to hero in Python. It’s packed with 22 hours of video material, plus coding ...

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

The best parallel processing libraries for Python Ray: Parallelizes and distributes AI and machine learning workloads across CPUs, machines, and GPUs. Dask: Parallelizes Python data science ...

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