Having helped hundreds of AI teams across a wide range of verticals, we have discovered some commonalities in their ML workflows that lead to long-term project success and greater scalability. Seeing first-hand the key roadblocks and best practices of the most successful ML teams, we wanted to share how they’ve utilized certain processes, standards, and tools to more skillfully master how they work with training data.

In this webinar, you will learn some of the training data practices used by the most successful AI teams and how these have been applied in production use cases. We’ll also be answering live Q&A from the audience so that you can tailor these lessons into your own MLOps and accelerate your AI journey.

Learn how leading AI teams accomplish more by leveraging:

  • Advanced collaboration between domain experts, labelers, and data scientists

  • APIs for smooth integrations and delegated access for better access to data

  • Interpreting model performance and prioritizing areas for iteration

  • Monitoring on labeling performance across project levels and individual levels

Watch now

Just some of companies that Labelbox is working with to build AI applications:

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Raphael Jafri

Senior MLSE, Labelbox

Featured Speakers

The training data practices used by the most successful AI teams


Just some of companies that Labelbox is working with to build AI applications:

Copyright 2021 - All Rights Reserved.

Privacy FAQ | Privacy Notice  | Cookie Notice | CCPA Notice | Terms of Use

ML Unboxed: How to diagnose and improve model performance

January 12: 11am PT

January 13: 8am PT/11am ET/4pm GMT

ML UNBOXED

Mark Ghannam

Solutions Engineer, EMEA, Labelbox