faisaltitu/Drift-Detection

feat: improve Monitor tab — Plotly charts, process-level metrics, project-scoped resources

mplement API metrics endpoint and rollback functionality

drift operations and simulation added

HF link added and readme updated

Replace HF setup instructions with live demo link

Architecture and readme updated

Update README architecture diagram to include Hugging Face Spaces

Add Hugging Face Spaces deployment configuration

add proper logginng and remove unnecessary characters

Add overlaid reference vs current distribution plots in drift analysis tab

Enhance dashboard: add Predict tab (input form) and Drift Analysis tab (KS + PSI charts)

Day 10: Finalize README with architecture diagram, screenshots, and setup instructions

Day 9: Fix all warnings (Pydantic namespace, sklearn feature names, MLflow import)

Day 9: Add CI/CD with GitHub Actions, pytest test suite (16 tests passing)

Day 8: Fix Docker build with host network, verify containers running

Day 8: Add Docker containerization with API and Dashboard Dockerfiles and docker-compose

Day 7: Add auto-retraining pipeline with drift-triggered retrain, promote, and API reload

Day 6: Add drift detection with KS-test, PSI, and drift simulation

Day 5: Add Streamlit monitoring dashboard with predictions table and charts

Day 4: Add FastAPI inference server with SQLite prediction logging

Day 3: Add MLflow tracking and model registry with production promotion

Day 2: Add training pipeline with preprocessing, training, and evaluation

Day 1: Initial project skeleton with folder structure