Back to the program

Project Jupyter is the evolution of iPython notebooks, applied to a range of different programming languages and environments. If you have not worked with Jupyter notebooks yet, here is a quick hands-on introduction. If you have already, this tutorial will also explore how Jupyter and Docker used together provide what Prof. Lorena Barba has called Computable Content. For examples, see [Oriole].

We will work through brief exercises that show how to use Jupyter notebooks, based an example application for natural language processing in Python. We will use [Launchbot] for preparing containers and notebooks locally. In other words, editing on a laptop prior to working at scale using Mesos or other cluster managers. We will walk through the system architecture used at O'Reilly Media to combine Apache Mesos, Marathon, Docker, and Jupyter. Then we will take in-depth look at how Jupyter is being used in industry, and consider its impact on data science, software engineering, and science in academia.