Optimizing Advertising Feature Evaluation Process with the Opal Machine Learning Platform

By migrating iQIYI’s advertising feature‑evaluation workflow to the Opal machine‑learning platform, the team replaced a manual, engineer‑heavy process with a unified, automated pipeline that cut evaluation cycles from five days to 1.5 days, tripling iteration speed while lowering barriers and improving consistency for future feature optimization.

Feature EvaluationModel OptimizationOpal Platform

0 likes · 6 min read

Optimizing Advertising Feature Evaluation Process with the Opal Machine Learning Platform

Didi Tech

Apr 26, 2021 · Artificial Intelligence

Model Quality Assurance Practices at DiDi: Challenges, Solutions, and Evaluation

DiDi’s shift to machine‑learning‑driven ride‑hailing services revealed major QA challenges—data and feature quality, model verification, and API stability—prompting a four‑pillar framework and a unified “Strategy‑Center 1.0” platform to systematically monitor, evaluate, and improve model effectiveness, bias paths, and feature discovery.

AI OperationsFeature EvaluationModel Evaluation

0 likes · 8 min read

Model Quality Assurance Practices at DiDi: Challenges, Solutions, and Evaluation