Machine Learning & Azure ML — AI-900 Practice Question
A representative Microsoft Azure AI Fundamentals (AI-900) exam question on Machine Learning & Azure ML. Work through it below, then read why each option is right or wrong.
Short answer
The correct answer is B. Automated Machine Learning (AutoML).
Automated Machine Learning (AutoML) automatically tests multiple algorithms and hyperparameter combinations to find the optimal model, saving significant manual experimentation time. Azure ML Designer (A) is a drag-and-drop interface for building pipelines but requires manual algorithm selection. Azure Databricks (C) is a big data analytics platform. Azure Cognitive Services (D) provides pre-built AI APIs, not custom model training.
The Question
A data scientist wants to quickly experiment with multiple algorithms and hyperparameters to find the best model for a classification problem, without manually coding each variation. Which Azure Machine Learning capability should they use?
Why B is correct
Automated Machine Learning (AutoML) automatically tests multiple algorithms and hyperparameter combinations to find the optimal model, saving significant manual experimentation time. Azure ML Designer (A) is a drag-and-drop interface for building pipelines but requires manual algorithm selection. Azure Databricks (C) is a big data analytics platform. Azure Cognitive Services (D) provides pre-built AI APIs, not custom model training.
Why the other options are wrong
Option A does not satisfy the requirement in the scenario. Review the explanation above: the correct choice (B) is the only one that fully meets every constraint stated in the question.
Option C does not satisfy the requirement in the scenario. Review the explanation above: the correct choice (B) is the only one that fully meets every constraint stated in the question.
Option D does not satisfy the requirement in the scenario. Review the explanation above: the correct choice (B) is the only one that fully meets every constraint stated in the question.
Key idea: Machine Learning & Azure ML
Automated Machine Learning (AutoML) automatically tests multiple algorithms and hyperparameter combinations to find the optimal model, saving significant manual experimentation time. Azure ML Designer (A) is a drag-and-drop interface for building pipelines but requires manual algorithm selection. Azure Databricks (C) is a big data analytics platform. Azure Cognitive Services (D) provides pre-built AI APIs, not custom model training. On the AI-900 exam, questions in the "Machine Learning on Azure" domain test whether you can map a scenario's constraints to the right choice. Read the requirement carefully, eliminate options that violate any single constraint, and pick the one that satisfies all of them with the least operational overhead.
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