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.
All guests are welcomed to register for the event.
This is a free event.