AI-900 Question 131
Single answerYou are a data scientist working on a machine learning project and need a scalable compute environment to train your model using large datasets. Additionally, you want to streamline the experiment tracking process and leverage pre-built machine learning algorithms. Which Azure service is most suitable for your requirements?
- A
Azure Machine Learning
- B
Azure Synapse Analytics
- C
Azure Data Lake Storage
- D
Azure Databricks
Show answer and explanation
Correct answer: A
Explanation
Azure Machine Learning is specifically designed to support the end-to-end machine learning lifecycle. It provides scalable compute environments for training models on large datasets, tools for experiment tracking, and access to pre-built machine learning algorithms, making it the most appropriate choice for the scenario described.
- A. Correct.
Azure Machine Learning provides a comprehensive platform for building, training, and deploying machine learning models. It includes scalable compute environments, experiment tracking, and access to pre-built algorithms, making it the most suitable choice for this scenario.
- B. Incorrect.
Azure Synapse Analytics is designed for data integration, analytics, and big data processing but does not offer specific features for training machine learning models or experiment tracking.
- C. Incorrect.
Azure Data Lake Storage is a storage solution for large-scale data but does not provide compute capabilities or machine learning features like experiment tracking or pre-built algorithms.
- D. Incorrect.
Azure Databricks is a collaborative analytics platform that supports machine learning but does not natively include features like experiment tracking or pre-built algorithms as seamlessly as Azure Machine Learning.