Model Explainability

Topic

Discover how you can see into the black box and explain what is happening with your algorithms.

AI algorithms are complicated by nature. It’s often difficult to understand – much less justify – their conclusions. But all is not lost. Emerging techniques for explaining algorithmic logic are shining a light into the black box.

Model explainability is not a silver bullet. However, these rapidly evolving capabilities are a critical tool in your AI toolkit.

Join Yannick Martel, AI & Analytics Lead at Capgemini, and SAS’ Brett Wujek as they discuss methods and best practices for explaining AI algorithms.

You will learn:
- Why model explainability is mandatory for machine learning in production.
- When to distinguish between local and global explanations.
- How model explanations help address bias.

SAS

Date

1 hour

Guest Policy

All guests are welcomed to register for the event.

Cost

This is a free event.

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