Jessica Forde, Yuvi Panda and Chris Holdgraf join Melanie and Mark to discuss Project Jupyter from it’s interactive notebook origin story to the various open source modular projects it’s grown into supporting data research and applications. We dive specifically into JupyterHub using Kubernetes to enable a multi-user server. We also talk about Binder, an interactive development environment that makes work easily reproducible.
Jessica Forde is a Project Jupyter Maintainer and a visiting academic at NYU Center for Data Science. Her research focus is applications that allow for human interaction, primarily in healthcare. Jessica is also a data scientist at Careful, a sports medicine startup. Her interest in industrial applications of reinforcement learning began at Columbia, where she developed energy-saving software for skyscrapers in Manhattan, which she demoed at NIPS. Previously, Jessica developed the DARPA-funded open source machine learning library, datamicroscopes, at Qadium. She has worked with consultants at McKinsey to provide data-driven human resources recommendations to clients.
Yuvi Panda is the Project Jupyter Technical Operations Architect in the UC Berkeley Data Sciences Division. He works on making it easy for people who don’t traditionally consider themselves “programmers” to do things with code. He builds tools (e.g., Quarry, PAWS, etc.) to sidestep the list of historical accidents that constitute the “command line tax” that people have to pay before doing productive things with computing.
Chris Holdgraf is a is a Project Jupyter Maintainer and Data Science Fellow at the Berkeley Institute for Data Science and a Community Architect at the Data Science Education Program at UC Berkeley. His background is in cognitive and computational neuroscience, where he used predictive models to understand the auditory system in the human brain. He’s interested in the boundary between technology, open-source software, and scientific workflows, as well as creating new pathways for this kind of work in science and the academy. He’s a core member of Project Jupyter, specifically working with JupyterHub and Binder, two open-source projects that make it easier for researchers and educators to do their work in the cloud. He works on these core tools, along with research and educational projects that use these tools at Berkeley and in the broader open science community.
Cool things of the week
Dragonball hosted on GC / powered by Spanner blog and GDC presentation at Developer Day
Cloud Text-to-Speech API powered by DeepMind WaveNet blog and docs
Now you can deploy to Kubernetes Engine from Gitlab blog
Binder site and docs
Kubernetes site github
Jupyter Notebook github
LIGO (Laser Interferometer Gravitational-Wave Observatory) site and binder
Paul Romer, World Bank Chief Economist blog and jupyter notebook
Data 8: The Foundations of Data Science site
Zero to JupyterHub site
JupyterHub Deploy Docker github
Jupyter Gitter channels
Jupyter Pop-Up, May 15th site
JupyterCon, Aug 21-24 site
Question of the week
How did Google’s predictions do during March Madness?
How to build a realt time prediction model: Architecting live NCAA predictions
Final Four halftime - fed data from first half to create prediction on second half and created a 30 second spot that ran on CBS before game play sample prediction ad
Kaggle Competition site
Where can you find us next?
Melanie is speaking about AI at Techtonica today, and April 14th
will be participating in a panel on Diversity and Inclusion at the Harker Research Symposium