Highlights from JupyterCon in New York 2017

Watch highlights covering Jupyter notebooks, data management, collaborative data science, and more. From JupyterCon in New York 2017.

By Mac Slocum
August 24, 2017
Andrew Odewahn (left) and Fernando Perez (right) at JupyterCon in New York 2017 Andrew Odewahn (left) and Fernando Perez (right) at JupyterCon in New York 2017 (source: O'Reilly Conferences via Flickr)

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

Jupyter at O’Reilly

Andrew Odewahn explains how O’Reilly Media applied the Jupyter architecture to create the next generation of technical content.

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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.

Jupyter and Anaconda: Shaking up the enterprise

Peter Wang talks about the co-evolution of Jupyter and Anaconda and looks at what’s needed to sustain an open and innovative future.

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.

Data science without borders

Wes McKinney makes the case for a shared infrastructure for data science.

Labz ‘N Da Wild 2.0: Teaching signal and data processing at scale using Jupyter notebooks in the cloud

Demba Ba explains how he designed and implemented two Harvard courses that use cloud-based Jupyter notebooks.

Making science happen faster

Jeremy Freeman describes a growing ecosystem of scientific solutions, many of which involve Jupyter.

Three movements driving enterprise adoption of Jupyter

William Merchan shares fundamental trends driving the adoption of Jupyter and its deployment in large organizations.

Design for reproducibility

Lorena Barba explores how we can build a capacity to support reproducible research into the design of tools like Jupyter.

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.

Post topics: Data
Post tags: Jupyter

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