ml-engineer-pro video for you have developed a Python module using Keras to train a regression model with two architectures: linear regression and deep neural
You have developed a Python module using Keras to train a regression model with two architectures: linear regression and deep neural network (DNN). The module utilizes the training_method argument to select the architecture, and for the DNN, it includes learning_rate and num_hidden_layers as hyperparameters. You plan to employ Vertex AI's hyperparameter tuning service with a budget of 100 trials to determine the optimal model architecture and hyperparameter values that minimize training loss and enhance performance. How should you proceed?