Kenta Murata
Kenta Murata

A full-time OSS developer at Speee Inc. I'm a committer of Apache Arrow and CRuby. I'm currently focusing on making Ruby a data-science-ready programming language.

Data visualization and machine learning using Ruby

Ruby finally had ready-to-use visualization and machine learning libraries. They are Charty and Rumale. I'd like to introduce them and demonstrate how to use them.

Using Charty, you get cool visualization results of your data by the smallest amount of code. The code amount is about 1 line in almost cases because Charty supports different types of data structures to visualize. You no longer need a conversion for visualization.

Rumale is a machine learning framework like scikit-learn. Rumale supports a lot of machine learning models. Rumale is written in Ruby so you don't need pycall.rb and Python environment to use machine learning models. If you want to do machine learning in your Ruby script, you must know how to use Rumale.

I'd like to realize the usefulness of Charty and Rumale by demonstration. You will realize that Ruby is no longer a programming language that cannot be used for data science.