Using NumPy for array and matrix math in Python Many mathematical operations, especially in machine learning or data science, involve working with matrixes, or lists of numbers.

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 ...

[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 ...

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 basic idea is to create an array of samples in a buffer using some features of SciPy’s NumPy component. Most regular waveforms are easy to create using an algorithm.

NumPy (and SciPy) do not have row operations implemented. Not to worry, we can do these ourself. To make it simpler to implement we'll use elementary matrices and matrix multiplication. The main idea ...

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 ...