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

Array programming, the heart of NumPy, is especially important in artificial intelligence programming, including machine learning and deep learning.

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 ...

Topics by chapter include: Setting up Python, NumPy, SciPy, OpenCV, OpenNI, and SensorKinect on Windows, Mac, and Ubuntu. Working with cameras, image/video files, and GUIs using OpenCV. Understanding ...

This NumPy version performs admirably, clocking in at around 28.77 ns per element -- almost two times faster than the pure Python rendition. Comparison established -- we have a clear winner. However, ...

In general, np.linspace(a,b,n+1) creates n + 1 points, a 0, a 1,, a n, starting at a and ending at b, each spaced out by Δ x = b a n, where a k = a 0 + k Δ x. Building Random Arrays NumPy has a few ...

[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 ...