ML Observability Workshop Series

Arize Workshop background

Taking a model from research to production is hard — and keeping it there is even harder! As more machine learning models are deployed into production, it’s imperative to have the right skillset to monitor, troubleshoot, and explain model performance. That’s why Arize is hosting an ML Observability Workshop Series to help data scientists and ML practitioners gain confidence taking their models from research to production.

Each week, we will cover a key area of ML Observability and practical applications. You will gain a hands-on understanding of how to identify where a model is underperforming, troubleshoot model and data issues, and how to proactively mitigate future degradations.

Upon completion of this series, you will receive a ML Observability Fundamentals acknowledgement for your new skills!

Register For the Series

This series occurs every Tuesday at 9am PST/12pm EST

Arize sessions:

ML Observability 101 Do you feel confident when taking models from research to production? Do you want to learn how to root cause model failure modes in production?
May 24th, 2022 , 9:00am -9:30am PST
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Performance Tracing with Arize Do you know the exact moment your models in production start to degrade? Is your team equipped to quickly and correctly root cause and resolve performance issues in production?
May 31st , 9:00am -9:30am PST
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Drift Detection with Arize Do you know the exact moment your production models start to decay? Are you able to correctly identify the type of drift which occurred and resolve it immediately?
June 7th , 9:00am -9:30am PST
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Data Quality Management with Arize Are you correctly identifying data quality issues in production data? Do you know the exact moment when your model inferences start to act up?
June 14th , 9:00am -9:30am PST
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Fairness & Bias Tracing with Arize Are you sure the ML models your company has in production are fair? Do you know if you are identifying model bias correctly and instantly in your current workflow?
June 21st , 9:00am -9:30am PST
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Feature Importance & Explainability with Arize Are you correctly leveraging explainability in your ML models? Do you know the level of explainability that is needed for your specific use case?
June 28th , 9:00am -9:30am PST
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Lunch and Learn / ML Observability 101 If you are an enterprise looking to learn more about ML Observability for your team we have something you might be interested in.
July 5th , 9:00am -9:30am PST
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Ready to level up your ML observability game?

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