What is the process of feeding a machine learning model with data to adjust its internal parameters and improve performance?Select one:a. Model trainingb. Model Validation

What is the purpose of training an ML model? a) To evaluate the model's performance b) To preprocess the input data c) To optimize the model's parameters d) To generate predictions

Data used to optimize the parameter settings of a supervised learner model is called ...............(1 Point)TestTrainingValidationNone of the above

How are model parameters optimized during training?Review LaterThey are set manually by the user.They are chosen through a search process.They are adjusted to minimize the discrepancy between model predictions and target values.They are fixed and do not change during training.

What is the primary purpose of a validation set in the context of model training?Select one:a. To test the model on unseen datab. To tune hyperparameters and evaluate model performance

What is used to refine the models during training?Batch NormalizationAdam OptimizerAll of the given optionsConv2DLeakyReLU