Microsoft Azure AI Fundamentals Machine Learning 5

Question 1

Which Azure service provides pre-built ML models via REST APIs without requiring any model training?

Accepted Answer

Azure Cognitive Services

Answer

Azure Cognitive Services offers pre-trained AI models for vision, speech, language, and decision-making, accessible via simple REST API calls without custom training.

Question 2

In the context of Azure ML, what is a 'model registry'?

Accepted Answer

A centralized repository for storing, versioning, and managing trained ML models

Answer

The Azure ML model registry is a centralized store that tracks all trained models with versioning, metadata, and lineage information for governance and deployment.

Question 3

Which machine learning technique combines predictions from multiple models to improve overall accuracy?

Accepted Answer

Ensemble learning

Answer

Ensemble learning combines outputs from multiple models (e.g., bagging, boosting, stacking) to produce a stronger, more accurate prediction than any single model.

Question 4

What is the primary purpose of normalization or standardization in machine learning data preparation?

Accepted Answer

Scaling features to a similar range so no single feature dominates training

Answer

Normalization and standardization scale numeric features to comparable ranges, preventing features with large values from disproportionately influencing model training.

Question 5

In Azure AutoML for NLP tasks, which scenario type would you choose to assign a single category to each text document?

Accepted Answer

Multi-class text classification

Answer

Multi-class text classification assigns exactly one class label per document, whereas multi-label allows multiple labels; NER extracts entities rather than classifying documents.

Microsoft Azure AI Fundamentals Practice Test

Microsoft Azure AI Fundamentals Practice Test

Microsoft Azure AI Fundamentals Machine Learning 5