Python is convenient and flexible, yet notably slower than other languages for raw computational speed. The Python ecosystem has compensated with tools that make crunching numbers at scale in Python ...

Let’s face it, robots are cool. They’re also going to run the world some day, and hopefully, at that time they will take pity on their poor soft fleshy creators (a.k.a. robotics developers) and help ...

Vectors, lists, arrays, matrices and data frames -- a look at five of the most fundamental data structures built into R. Among my colleagues, R is one of the fastest-growing programming languages.

It took the programming community a couple of decades to appreciate Python. But since the early 2010’s, it has been booming — and eventually surpassing C, C#, Java and JavaScript in popularity. But ...

Introduction -- Why use R for your statistical work? -- Whom is this book for? -- My own background -- Getting started -- How to run R -- A first R session -- Introduction to functions -- Preview of ...

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 ...

A lot of software developers are drawn to Python due to its vast collection of open-source libraries. Lately, there have been a lot of libraries cropping up in the realm of Machine Learning (ML) and ...

Programming model moves from managing thousands of low-level threads to working with high-level ‘tiles of data’ ...