ML System Design
Designing ML systems: method, case studies, estimation and experiments
Open "Foundations and Method"
Foundations and Method
Metrics, features, serving, rollout, monitoring and the interview framework
20 questions
Open "Case Studies"
Case Studies
End-to-end case studies: recommendations, search, fraud detection, moderation, demand forecasting, pricing, ads
20 questions
Open "Estimation and Experiments"
Estimation and Experiments
Back-of-the-envelope estimates, A/B design and sizing, interference, sensitivity, interview conduct
20 questions