Which of the following sentences is true about model evaluation and model validation in ML pipelines?

Model validation is the process of checking whether the model meets the specified requirements

and quality standards. It involves testing the model on a validation dataset, which is different from

the training and testing datasets, and evaluating the model performance using appropriate metrics.

Reference: Overview of ML Pipelines | Machine Learning, MLOps: Continuous delivery and

automation pipelines in machine learning