Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA

Jupyter sessions, sponsored by IBM

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11:00am11:40am Wednesday, March 27, 2019
Sponsored
Location: 2014
Alan Chin (IBM), LUCIANO RESENDE (IBM)
Average rating: ****.
(4.75, 4 ratings)
Alan Chin and Luciano Resende explain how to introduce Jupyter Enterprise Gateway into new and existing notebook environments to enable a "bring your own notebook" model while simultaneously optimizing resources consumed by the notebook kernels running across managed clusters within the enterprise. Read more.
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11:50am12:30pm Wednesday, March 27, 2019
Sponsored
Location: 2014
Omoju Miller (GitHub)
Average rating: ***..
(3.50, 10 ratings)
GitHub has a relatively nascent ML group. Its major challenge is to integrate ML product building processes into a mature product engineering org. This means that it's responsible for building end-to-end ML products, from ETL to production. Omoju Miller details the many roles Jupyter notebooks play in the building of ML products. Read more.
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2:40pm3:20pm Wednesday, March 27, 2019
Sponsored
Location: 2014
M Pacer (Netflix)
Average rating: ****.
(4.57, 7 ratings)
M Pacer discusses two meanings of "Talking with Jupyter": talking to others with Jupyter notebooks and talking to Jupyter in the language of its standards, formats, and protocols. M describes tools, workflows, and patterns that make both kinds of talking with Jupyter easier while unlocking new ways of interacting with the Jupyter ecosystem. Read more.
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4:20pm5:00pm Wednesday, March 27, 2019
Sponsored
Location: 2014
Chris Holdgraf (Berkeley Institute for Data Science)
Average rating: ****.
(4.75, 4 ratings)
Chris Holdgraf shares recent tools from the Jupyter project in partnership with UC Berkeley that facilitate communication with Jupyter and get us closer to displaying notebook-style content in a more discoverable and reader-friendly form—allowing you to turn collections of notebooks into an online book and connect this content with the cloud in order to make your online content interactive. Read more.
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5:10pm5:50pm Wednesday, March 27, 2019
Sponsored
Location: 2014
Average rating: ***..
(3.43, 7 ratings)
Project Jupyter is very popular for data science, data exploration, and visualization. Manu Mukerji and Justin Driemeyer explain how to use it for AI/ML in a production environment. Read more.