Explore static, dynamic, and online learning models with hands-on demonstrations in the ecosystem.Ai Workbench to see how each works in practice.
| City | Time |
|---|---|
| San Francisco (UTC−7) | 8:00 AM |
| New York (UTC−4) | 11:00 AM |
| London (UTC+1) | 4:00 PM |
| Johannesburg / Cape Town (UTC+2) | 5:00 PM |
Different machine learning possess different strengths. Therefore, choosing the right type can make or break your project. In this session, we’ll explore the differences between static and dynamic models.
Using the ecosystem.Ai Workbench and Prediction Platform, we’ll demonstrate how each model type is configured and applied to real use cases. From simple static predictions to dynamic systems, you’ll learn how different approaches support different business needs. Expect a practical, technical walk-through designed to connect data science concepts with real-world deployment.
http://meet.google.com/eit-prds-gbg
