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.

By Mac Slocum
August 24, 2018
New York Skyline - JupyterCon 2018 New York Skyline - JupyterCon 2018

People from across the Jupyter community came together in New York for JupyterCon. Below you’ll find links to keynotes from the event.

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.

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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.

Jupyter in the enterprise

Luciano Resende explores some of the open source initiatives IBM is leading in the Jupyter ecosystem.

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.

Machine learning and AI technologies and platforms at AWS

Dan Romuald Mbanga walks through the ecosystem around the machine learning platform and API services at AWS.

Democratizing data

Tracy Teal explains how to bring people to data and empower them to address their questions.

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.

Beyond interactive: Scaling impact with notebooks at Netflix

Michelle Ufford shares how Netflix leverages notebooks today and describes a brief vision for the future.

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.

Disease prediction using the world’s largest clinical lab data set

Cristian Capdevila explains how Prognos is predicting disease.

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.

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.

Post topics: Data
Post tags: Jupyter

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