AI-900 Question 133
Single answerYou are a data scientist working on a machine learning project that requires training a large dataset using scalable compute resources. Which Azure service would you use to manage the training environment and orchestrate the machine learning workflows?
- A
Azure Machine Learning
- B
Azure Synapse Analytics
- C
Azure Data Lake Storage
- D
Azure IoT Hub
Show answer and explanation
Correct answer: A
Explanation
Azure Machine Learning is the best choice for managing machine learning workflows and training environments because it offers scalable compute resources, integrated tools for experimentation, and orchestration capabilities. Other services like Azure Synapse Analytics, Azure Data Lake Storage, and Azure IoT Hub are specialized for different purposes and do not provide the necessary features for machine learning workflows.
- A. Correct.
Azure Machine Learning is a comprehensive service that provides tools for managing machine learning workflows, including model training, deployment, and monitoring. It is specifically designed for data science and machine learning tasks.
- B. Incorrect.
Azure Synapse Analytics is primarily used for data integration, big data analysis, and data warehousing, but it is not designed to manage machine learning workflows or training environments.
- C. Incorrect.
Azure Data Lake Storage is a storage service optimized for big data analytics, but it does not provide compute resources or workflow management for machine learning.
- D. Incorrect.
Azure IoT Hub is used for managing IoT devices and processing IoT data streams. It is not relevant for machine learning workflows or compute resource orchestration.