Jupyter notebooks are a new increasingly popular way of doing data science. They are documents that contain both computer code (e.g. python, java) and rich text elements (paragraph, equations, figures, links, etc…). Jupyter notebook documents are both human-readable documents containing the analysis description and the results (figures, tables, etc..) as well as executable documents which can be run to perform data analysis.

Now, it is possible to create Jupyter notebooks with MOA, using a Java kernel, like the IJava kernel.

This is a Jupyter notebook example that you can execute and modify online:
https://mybinder.org/v2/gh/abifet/moa-notebooks/master?filepath=MOA-Prequential-Evaluation.ipynb

The source code is in github: https://github.com/abifet/moa-notebooks

Here, you can find its nbviewer visualization: