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Learning Jupyter by Dan Toomey

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Summary

In this chapter, we learned how to add JavaScript to our Jupyter Notebook. We saw some of the limitations of using JavaScript in Jupyter. We had a look at examples of several packages that are typical of Node.js coding, including 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.

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