Learn the NumPy trick for generating synthetic data that actually behaves like real data.

There is a phenomenon in the Python programming language that affects the efficiency of data representation and memory. I call it the "invisible line." This invisible line might seem innocuous at ...

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. Over the past few months, the use of the Python programming ...

For the past few months, I've been covering different software packages for scientific computations. For my next several articles, I'm going to be focusing on using Python to come up with your own ...

These pages provide a showcase of how to use Python to do computations from linear algebra. We will demonstrate both the NumPy (SciPy) and SymPy packages. This is meant to be a companion guide to a ...

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 data in ...

This is new: TensorFlow 2.18 integrates the current version 2.0 of NumPy and, with Hermetic CUDA, will no longer require local CUDA libraries during the build. The ...

Although neural networks have been studied for decades, over the past couple of years there have been many small but significant changes in the default techniques used. For example, ReLU (rectified ...