PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #301
PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #301: Real Exam Question with Answer & Explanation
Sign in or unlock PROFESSIONAL-MACHINE-LEARNING-ENGINEER to reveal the answer and full explanation for question #301. The question stem and answer options stay visible for context.
Question
You developed a Python module by using Keras to train a regression model. You developed two model architectures, linear regression and deep neural network (DNN), within the same module. You are using the training_method argument to select one of the two methods, and you are using the learning_rate and num_hidden_layers arguments in the DNN. You plan to use Vertex AI's hypertuning service with a budget to perform 100 trials. You want to identify the model architecture and hyperparameter values that minimize training loss and maximize model performance. What should you do?
Options
- ARun one hypertuning job for 100 trials. Set num_hidden_layers as a conditional
- BRun two separate hypertuning jobs, a linear regression job for 50 trials, and a DNN job for 50 trials.
- CRun one hypertuning job with training_method as the hyperparameter for 50 trials. Select the
- DRun one hypertuning job for 100 trials. Set and as
Unlock PROFESSIONAL-MACHINE-LEARNING-ENGINEER to see the answer
You've previewed enough free PROFESSIONAL-MACHINE-LEARNING-ENGINEER questions. Unlock PROFESSIONAL-MACHINE-LEARNING-ENGINEER for full answers, explanations, the timed quiz mode, progress tracking, and the master PDF. Question stem and options stay visible so you can still see what's on the exam.