Date: Wed, 11 Apr 2018 00:00:00 +0000
<p><a href="https://github.com/jzf2101">Jessica Forde</a>, <a href="https://twitter.com/yuvipanda">Yuvi Panda</a> and <a href="https://twitter.com/choldgraf">Chris Holdgraf</a> join <a href="https://twitter.com/nyghtowl">Melanie</a> and <a href="https://twitter.com/Neurotic">Mark</a> 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.</p> <h5 id="jessica-forde">Jessica Forde</h5> <p><a href="https://github.com/jzf2101">Jessica Forde</a> is a Project Jupyter Maintainer with a background in reinforcement learning and Bayesian statistics. At Project Jupyter, she works primarily on JupyterHub, Binder, and JuptyerLab to improve access to scientific computing and scientific research. Her previous open source projects include datamicroscopes, a DARPA-funded Bayesian nonparametrics library in Python, and density, a wireless device data tool at Columbia University. Jessica has also worked as a machine learning researcher and data scientist in a variety of applications including healthcare, energy, and human capital.</p> <h5 id="yuvi-panda">Yuvi Panda</h5> <p><a href="https://twitter.com/yuvipanda">Yuvi Panda</a> 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.</p> <h5 id="chris-holdgraf">Chris Holdgraf</h5> <p><a href="https://twitter.com/choldgraf">Chris Holdgraf</a> 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.</p> <h5 id="cool-things-of-the-week">Cool things of the week</h5> <ul> <li>Dragonball hosted on GC / powered by Spanner <a href="https://techcrunch.com/2018/03/20/bandai-namco-bets-on-google-cloud-to-power-its-new-pvp-dragon-ball-game/"> blog</a> and <a href="https://www.youtube.com/watch?v=5wtlj_q3DjE&feature=youtu.be&t=20497"> GDC presentation at Developer Day</a></li> <li>Cloud Text-to-Speech API powered by DeepMind WaveNet <a href="https://cloudplatform.googleblog.com/2018/03/introducing-Cloud-Text-to-Speech-powered-by-Deepmind-WaveNet-technology.html"> blog</a> and <a href="https://cloud.google.com/text-to-speech/">docs</a></li> <li>Now you can deploy to Kubernetes Engine from Gitlab <a href="https://cloudplatform.googleblog.com/2018/04/now-you-can-deploy-to-Kubernetes-Engine-from-GitLab-with-a-few-clicks.html"> blog</a></li> </ul> <h5 id="interview">Interview</h5> <ul> <li>Jupyter <a href="http://jupyter.org/">site</a></li> <li>JupyterHub <a href="https://github.com/jupyterhub/jupyterhub">github</a></li> <li>Binder <a href="https://mybinder.org/">site</a> and <a href="http://binder.readthedocs.io/en/latest/">docs</a></li> <li>JupyterLab <a href="https://github.com/jupyterlab/jupyterlab">site</a></li> <li>Kubernetes <a href="https://kubernetes.io">site</a> <a href="https://github.com/kubernetes/kubernetes">github</a></li> <li>Jupyter Notebook <a href="https://github.com/jupyterlab">github</a></li> <li>LIGO (Laser Interferometer Gravitational-Wave Observatory) <a href="https://www.ligo.caltech.edu/">site</a> and <a href="https://github.com/minrk/ligo-binder">binder</a></li> <li>Paul Romer, World Bank Chief Economist <a href="https://paulromer.net/doing-business/">blog</a> and <a href="https://github.com/paulromer149/DB-Calcs/blob/master/DB-Calcs.ipynb"> jupyter notebook</a></li> <li>The Scientific Paper is Obsolete <a href="https://www.theatlantic.com/science/archive/2018/04/the-scientific-paper-is-obsolete/556676/?single_page=true"> article</a></li> <li>Large Scale Teaching Infrastructure with Kubernetes - Yuvi Panda, Berkeley University <a href="https://www.youtube.com/watch?v=g5rl7T18n-s">video</a></li> <li>Data 8: The Foundations of Data Science <a href="http://data8.org/">site</a></li> <li>Zero to JupyterHub <a href="https://zero-to-jupyterhub.readthedocs.io/en/latest/">site</a></li> <li>JupyterHub Deploy Docker <a href="https://github.com/jupyterhub/jupyterhub-deploy-docker">github</a></li> <li>Jupyter Gitter <a href="https://gitter.im/jupyter/home">channels</a></li> <li>Jupyter Pop-Up, May 15th <a href="https://www.eventbrite.com/e/jupyter-pop-up-dc-tickets-44090939186?aff=jcwebsite"> site</a></li> <li>JupyterCon, Aug 21-24 <a href="https://conferences.oreilly.com/jupyter/jup-ny">site</a></li> </ul> <div style="text-align: center;"><a href="http://jupyter.org/"><img src="https://googlecloudpodcast.libsyn.com/images/post/jupyter.png" style="margin: auto;" /></a></div> <h5 id="question-of-the-week">Question of the week</h5> <p>How did Google’s predictions do during March Madness?</p> <ul> <li>How to build a realt time prediction model: <a href="https://cloud.google.com/blog/big-data/2018/03/architecting-live-ncaa-predictions-from-archives-to-insights"> Architecting live NCAA predictions</a></li> <li>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 <a href="http://creativity-online.com/work/google-villanova-vs-michigan-2nd-half-realtime-prediction/54248"> sample prediction ad</a></li> <li>Kaggle Competition <a href="https://www.kaggle.com/c/mens-machine-learning-competition-2018">site</a></li> </ul> <h5 id="where-can-you-find-us-next">Where can you find us next?</h5> <ul> <li>Melanie is speaking about AI at <a href="https://techtonica.org">Techtonica</a> today, and April 14th will be participating in a panel on Diversity and Inclusion at the <a href="https://www.harker.org/about/events/research-symposium#bookmark-intro"> Harker Research Symposium</a></li> </ul>