Model Deployment

Process of bringing trained models into production.

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Model deployment includes all steps required to make a trained model available in a production environment for real-time or batch predictions.

• Key aspects: Containerization, APIs, scalability, monitoring.
• Goal: Ensure reliable and efficient AI operations.