d3 for graphics,
stats-analysis for statistics, built-in JSON handling,
canvas for creating graphics files, and
plotly used for generating graphics with a third party tool. We also saw how multi-threaded applications can be developed using Node.JS under Jupyter. Lastly, we saw how to use machine learning to develop a decision tree.
In the next chapter, we will see how to create interactive widgets that can be used in your notebook.