ML monitoring platform
ModelOps Doctor
Model health, data drift, and diagnosis in one practical control room.
Project by Akabir Abbas · Public project
The problem
Prediction logs, model records, and data drift are difficult to review when monitoring information is spread across separate tools.
My contribution
Python monitoring workflows covering model and dataset registration, prediction-log ingestion, health scoring, and scheduled background jobs.
What I built
Registers models and datasets, ingests prediction logs, computes health scores, and schedules monitoring workflows with clear retraining guidance.
Technologies used
Implementation outcome
The platform brings model health, drift diagnosis, and retraining guidance into a single monitoring workflow. The public repository provides implementation evidence.
This describes the implemented functionality. Quantitative benchmarks and business-impact measurements are not published for this project.