JupyterHub is an important tool for research and data-driven decisions at Globo.com. Diogo Munaro Vieira and Felipe Ferreira explain how data scientists at Globo.comthe largest media group in Latin America and second largest television group in the worlduse Jupyter notebooks for data analysis and machine learning, making decisions that impact 50 million users per month.

Scientific research thrives on collaborations between computational and experimental groups, who work together to solve problems using their separate expertise. Zach Sailer highlights how tools like the Jupyter Notebook, JupyterHub, and ipywidgets can be used to make these collaborations smoother and more effective.

Shreyas Cholia, Rollin Thomas, and Shane Canon share their experience leveraging JupyterHub to enable notebook services for data-intensive supercomputing on the Cray XC40 Cori system at the National Energy Research Scientific Computing Center (NERSC).

Demba Ba discusses two new signal processing/statistical modeling courses he designed and implemented at Harvard, exploring his perspective as an educator and that of the students as well as the steps that led him to adopt the current cloudJHub architecture. Along the way, Demba outlines the potential of architectures such as cloudJHub to help to democratize data science education.