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ML Observability Workshop Series

Virtual San Francisco

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!

Voices of ML Leaders

Virtual San Francisco

When it comes to aligning the data science team with the business, recruiting and retaining talents, and applying the most beneficial AI methodologies, AI leaders set up initiatives and are...

Drift Happens featuring Pujaa Rajan of Stripe

Virtual San Francisco

Join us Thursday, June 16th, 4pm ET/ 1pm PT for Drift Happens, Arize’s weekly video chat where our host Amber Roberts will discuss ML use cases, best practices in model...

The Future of Data-Centric AI

Virtual San Francisco

A free virtual event to explore data-centric approaches that make AI practical. Hosted by Snorkel AI

Ray Summit 2022

San Francisco, CA San Francisco, CA