CodeNFacts ML Pipeline
A modular end-to-end workflow for production-ready machine learning.
Data Ingestion
Collecting raw data from SQL, APIs, and CSV sources.
Exploration
Feature engineering and data cleaning process.
Model Training
Training XGBoost or Random Forest models.
Evaluation
Validating accuracy, precision, and recall.
Deployment
Hosting the model via FastAPI or Streamlit.
Pipeline Status
| Component | Status | Last Run | Artifacts |
|---|---|---|---|
| Pre-processing | ● Success | 2 hours ago | features.pkl |
| Training | ● Success | 1 hour ago | model_v1.bin |