Jupyter Notebook x Docker to Production on Heroku

A boilerplate to transform research notebooks into production-level code which uses the a Kaggle dataset on customer churn.

We have used the new hierarchical carbonate reservoir benchmarking case study created by Costa Gomes J, Geiger S, Arnold D to be used for reservoir characterization, uncertainty quantification and history matching.

📚 Jupyter Notebooks extension for versioning, managing and sharing notebook checkpoints in your machine learning and data science projects.

Create plug-ins that expand and enhance the functionality of the i2 Notebook web client by using the i2 Notebook SDK. The SDK is comprised of documentation, tools, and sample code.