Mar 15–18, 2020

Schedule: Machine Learning Model Governance and Operations sessions

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9:00am12:30pm Monday, March 16, 2020
Location: LL21 D
Danilo Sato (ThoughtWorks)
Danilo Sato lead you through applying continuous delivery (CD) to data science and machine learning (ML). Join in to learn how to make changes to your models while safely integrating and deploying them into production using testing and automation techniques to release reliably at any time and with a high frequency. Read more.
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1:30pm5:00pm Monday, March 16, 2020
Location: LL21 C
Boris Lublinsky (Lightbend), Dean Wampler (Anyscale)
Machine learning (ML) models are data, which means they require the same data governance considerations as the rest of your data. Boris Lublinsky and Dean Wampler outline metadata management for model serving and explore what information about running systems you need and why it's important. You'll also learn how Apache Atlas can be used for storing and managing this information. Read more.
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1:30pm5:00pm Monday, March 16, 2020
Location: LL21 E/F
Patrick Hall (H2O.ai | George Washington University)
Even if you've followed current best practices for model training and assessment, machine learning models can be hacked, socially discriminatory, or just plain wrong. Patrick Hall breaks down model debugging strategies to test and fix security vulnerabilities, unwanted social biases, and latent inaccuracies in models. Read more.

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