Microsoft Azure AI Fundamentals AI-900 Practice Question

To evaluate the model during training and adjust hyperparameters - This is the correct answer. The validation dataset is used to evaluate the model's performance on unseen data during the training process and to help tune the model's hyperparameters, such as learning rate and regularization. This helps to ensure the model generalizes well to new data.

To train the model by fitting its parameters to this data - This is incorrect. This is the purpose of the training dataset, which is used to fit the model's parameters and allow the model to learn from the data.

To test the model's performance after training is complete - This is incorrect. This describes the function of the test dataset, which is used to provide a final, unbiased evaluation of the model's performance after all training and hyperparameter tuning is complete.

To provide additional features for the model - This is incorrect. The validation dataset consists of the same features as the training data. Its purpose is for evaluation, not for introducing new features to the model.