ML System Design
for Continuous Experimentation

In this webinar, we will:

• Examine some naive ML workflows that don’t take the development-production feedback loop into account and explore why they break down.
• Showcase some system design principles that will help manage these feedback loops more effectively.
• Explore several industry case studies where teams have applied these principles to their production ML systems.