Pharo is a remarkably versatile programming language. It can be used for nearly anything, like back-end web (with Seaside or Teapot), front-end web (with Amber or PharoJS), mobile (with Amber or PharoJS, and Cordova/PhoneGap), machine learning (with Pharo language bindings for TensorFlow), IoT (with PharoThings), robotics (for example, PhaROS), virtual reality (for example, Virtual Reality Live at Thales), enterprise business computing (for example, JP Morgan and OOCL), etc.
In this post, I’d like to focus your attention on using Pharo for data science. PolyMath is a NumPy-like library for computational science. I mention NumPy because Python is today’s “go to” language for data science. However, Python isn’t the only game in town, and alternative languages like Pharo and Julia have much to offer.
Pharo’s data visualization capability is especially noteworthy. Roassal is one of the best tools in this regard. The following video gives you a taste for the latest version of Roassal:
For more advanced users, here’s a terrific book on Numerical Methods with Pharo.
I hope this inspires you to learn Pharo.