Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
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From Jupyter to production: Accelerating solutions to business problems in production

5:10pm5:50pm Wednesday, March 27, 2019
Location: 2014
Secondary topics:  Jupyter
Average rating: ***..
(3.43, 7 ratings)

Who is this presentation for?

  • Current Jupyter users interested in learning how Jupyter can be used in production

Prerequisite knowledge

  • A basic understanding of AI, ML, and Project Jupyter

What you'll learn

  • Understand considerations for creating a production AI/ML system


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.

Topics include:

  • How things can go wrong with QA and production releases when using a notebook
  • Common Jupyter ML examples
  • Standard ML flow
  • Training in production
  • Model creation
  • You have a model. Now what?
  • Keeping Jupyter out of production
  • Papermill and Jupyter
  • Production workflows with SageMaker
  • How it all fits together
Photo of Manu Mukerji

Manu Mukerji


Manu Mukerji is senior director of data, machine learning, and analytics at 8×8. Manu’s background lies in cloud computing and big data, working on systems handling billions of transactions per day in real time. He enjoys building and architecting scalable, highly available data solutions and has extensive experience working in online advertising and social media.

Justin Driemeyer


Justin Driemeyer is an ML staff engineer at 8×8. Previously, he spent three years at an ML B2B advertising startup (acquired by 8×8) and seven years at Zynga, as it went from a 10-person startup to a 2,000-person public company. He holds a BS in computer engineering from U of I and an MS in CS from Stanford, where he worked on the STAIR project.