Sea change: What happens when Jupyter becomes pervasive at a university?
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.
Jupyter
The future of data-driven discovery in the cloud
Ryan Abernathey makes the case for the large-scale migration of scientific data and research to the cloud.
Jupyter notebooks and the intersection of data science and data engineering
David Schaaf explains how data science and data engineering can work together to deliver results to decision makers.
Data science as a catalyst for scientific discovery
Michelle Gill discusses how data science methods and tools can link information from different scientific fields and accelerate discovery.
Democratizing data
Tracy Teal explains how to bring people to data and empower them to address their questions.
Highlights from JupyterCon in New York 2018
Watch keynotes covering Jupyter's role in business, data science, higher education, open source, journalism, and other domains, from JupyterCon in New York 2018.
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.
Jupyter trends in 2018
Paco Nathan shares a few unexpected things that emerged in Jupyter in 2018.
Sustaining wonder: Jupyter and the knowledge commons
Carol Willing shows how Jupyter's challenges can be addressed by embracing complexity and trusting others.
The reporter’s notebook
Mark Hansen explains how computation has forever changed the practice of journalism.
Why contribute to open source?
Julia Meinwald outlines effective ways to support the unseen labor maintaining a healthy open source ecosystem.
Making science happen faster
Jeremy Freeman describes a growing ecosystem of scientific solutions, many of which involve Jupyter.
Design for reproducibility
Lorena Barba explores how we can build a capacity to support reproducible research into the design of tools like Jupyter.
Jupyter at O’Reilly
Andrew Odewahn explains how O’Reilly Media applied the Jupyter architecture to create the next generation of technical content.
The give and take of open source
Brett Cannon looks at how healthy expectations can maintain a balanced relationship between open source users and project maintainers.
Where money meets open source
Nadia Eghbal explores how money can support open source development without changing its incentives.
Project Jupyter: From interactive Python to open science
Fernando Perez explains how Project Jupyter fits into a vision of collaborative development of tools that are applicable to research, education, and industry.
How the Jupyter Notebook helped fast.ai teach deep learning to 50,000 students
Rachel Thomas shares her experience using Jupyter notebooks to help students understand deep learning through experimentation.