Tune Hyperparameters and Deploy Trained Models for Inference in Applied Scenarios

Learning Objectives

At the end of this theory note, trainees must be able to:

1. Distinguish hyperparameters from model parameters and explain their effect on performance.
2. Apply systematic optimisation techniques to tune hyperparameters.
3. Validate and finalise an optimised model against defined performance requirements.
4. Save and package a trained model using appropriate serialisation tools.
5. Build an inference endpoint to serve predictions in an applied scenario.
6. Document a deployment process and its results in accordance with industry practice.