AI-900 Question 122
Single answerA data scientist wants to build and train a machine learning model using Azure Machine Learning. They need a feature that allows them to automate the process of hyperparameter tuning to improve the model's performance. Which Azure Machine Learning capability should they use?
- A
Automated Machine Learning (AutoML)
- B
HyperDrive
- C
Azure Cognitive Services
- D
Azure Data Factory
Show answer and explanation
Correct answer: B
Explanation
HyperDrive is a feature of Azure Machine Learning designed specifically for hyperparameter optimization. It enables data scientists to automate the process of running multiple experiments with different hyperparameter combinations to find the best-performing model. This makes it the ideal choice for the scenario described in the question.
- A. Incorrect.
Automated Machine Learning (AutoML) assists in automating the end-to-end machine learning process, including model selection and feature engineering, but it does not specifically focus on hyperparameter tuning for custom training scripts.
- B. Correct.
HyperDrive is the correct answer because it is an Azure Machine Learning capability that allows you to perform hyperparameter tuning to optimize your machine learning models.
- C. Incorrect.
Azure Cognitive Services is a collection of pre-built AI services for tasks like vision, speech, and language, but it does not provide hyperparameter tuning for machine learning models.
- D. Incorrect.
Azure Data Factory is a data integration service for building ETL pipelines and does not provide any machine learning-specific capabilities like hyperparameter tuning.