[Avg. reading time: 2 minutes]
Examples
Retail:
- Traditional ML -> Demand forecasting.
- GenAI -> Personalized product descriptions.
- MLOps -> Continuous retraining as seasons change.
Healthcare:
- Traditional ML -> Predict patient readmission.
- GenAI -> Auto-generate clinical notes.
- MLOps -> Ensure compliance & monitoring under HIPAA.
Finance:
- Traditional ML -> Fraud detection.
- GenAI -> AI-powered customer chatbots.
- MLOps -> Drift detection for fraud models.
| Traditional ML | GenAI | MLOps |
|---|---|---|
| Fraud detection (transaction classification) | AI-powered customer chatbots for support | Drift detection & alerts for fraud models |
| Credit scoring (loan approval risk models) | Personalized financial advice reports | Automated retraining with new credit bureau data |
| Stock price trend prediction | Summarizing financial reports & earnings calls | Compliance monitoring (audit trails for regulators) |
| Customer lifetime value prediction | Generating personalized investment recommendations | Model versioning & rollback in case of errors |