Completed
Why managing ML products is hard
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
ML Teams and Project Management - FSDL 2022
Automatically move to the next video in the Classroom when playback concludes
- 1 Why managing ML products is hard
- 2 Roles in ML teams: MLEs, MLRs, DSs
- 3 Hiring and getting hired in ML
- 4 Organizational archetypes: from ad hoc ML to ML-first
- 5 Building ML teams
- 6 Managing ML teams and products
- 7 How to manage ML projects better
- 8 "Managing up" in ML
- 9 ML PMs are well-positioned to educate the org
- 10 What is the "Agile for ML"?
- 11 Best practices for ML product design
- 12 Summary
