MLOps in Practice: Common Challenges and Lessons Learned - Meetup 114

Explore common challenges and lessons learned in MLOps through this insightful conference talk featuring Machine Learning Reply's Senior Consultants Marouen Hizaoui and Mo Basirati. Gain valuable insights into practical MLOps implementation, including the importance of non-technical aspects, choosing appropriate tools, and integrating MLOps into systems with varying maturity levels. Learn from real-world stories and experiences shared by the speakers, covering topics such as model packaging, maintaining standards across teams, redefining processes, and the significance of architecture in MLOps projects. Discover strategies for starting simple yet effective MLOps practices and understand the key components of a robust MLOps architecture. This comprehensive discussion also touches on the challenges of managing multiple components in MLOps pipelines, providing a well-rounded perspective on the field.

[] Musical Introduction to Marouen Hizaoui & Mo Basirati
[] MLOps in Practice: Common Challenges and Lessons Learned
[] Agenda
[] Machine Learning Reply
[] What MLOps is to Reply
[] MLOps Stories
[] Story: Packaging Model
[] Maintaining standards and compliances across teams of Reply
[] Redefining processes
[] Project Setting
[] Story: Start simple, but start
[] Story: Architecture Matters
[] Main components of the architecture
[] Views on having many components in the pipeline
[] Wrap up