Fernando Perez talks about UC Berkeley's transition into an environment where many undergraduates use Jupyter and the open data ecosystem as naturally as they use email.
Michelle Ufford shares how Netflix leverages notebooks today and describes a brief vision for the future.
David Schaaf explains how data science and data engineering can work together to deliver results to decision makers.
Ryan Abernathey makes the case for the large-scale migration of scientific data and research to the cloud.
Michelle Gill discusses how data science methods and tools can link information from different scientific fields and accelerate discovery.
Tracy Teal explains how to bring people to data and empower them to address their questions.
Cristian Capdevila explains how Prognos is predicting disease.
Dan Romuald Mbanga walks through the ecosystem around the machine learning platform and API services at AWS.
Paco Nathan shares a few unexpected things that emerged in Jupyter in 2018.
Carol Willing shows how Jupyter's challenges can be addressed by embracing complexity and trusting others.
Luciano Resende explores some of the open source initiatives IBM is leading in the Jupyter ecosystem.
Mark Hansen explains how computation has forever changed the practice of journalism.
Julia Meinwald outlines effective ways to support the unseen labor maintaining a healthy open source ecosystem.
All the cool kids are doing it, maybe we should too? Jupyter, gravitational waves, and the LIGO and Virgo Scientific Collaborations
Will Farr offers lessons about the many advantages and few disadvantages of using Jupyter for global scientific collaborations.