Microsoft Azure AI Fundamentals MCQ Flashcards
7 cards from real Microsoft Azure AI Fundamentals practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Microsoft Azure AI Fundamentals MCQ flashcards as text
Which Azure service provides pre-built AI models for vision, speech, language, and decision tasks without requiring ML expertise?
Answer: Azure Cognitive Services
Azure Cognitive Services offers pre-built AI APIs for common AI tasks that developers can integrate without training custom models.
A company wants to detect whether a customer review is positive, negative, or neutral. Which AI technique is most appropriate?
Answer: Sentiment analysis
Sentiment analysis is an NLP technique that determines the emotional tone of text, categorizing it as positive, negative, or neutral.
What does the term 'overfitting' mean in the context of machine learning?
Answer: The model performs well on training data but poorly on new data
Overfitting occurs when a model learns the training data too well, including its noise, causing poor generalization to unseen data.
Which Azure AI service would you use to extract text from scanned documents and images?
Answer: Azure Form Recognizer
Azure Form Recognizer (now Document Intelligence) uses AI to extract text, key-value pairs, and tables from documents and images.
In responsible AI, which principle ensures that AI systems are transparent about how they make decisions?
Answer: Explainability
Explainability (also called transparency) ensures that AI decision-making processes can be understood and interpreted by humans.
Which type of machine learning involves learning from labeled training data to predict outcomes for new inputs?
Answer: Supervised learning
Supervised learning uses labeled datasets where the correct outputs are known to train models that can predict outcomes for new, unseen inputs.
What is the primary purpose of Azure Machine Learning's automated ML (AutoML) feature?
Answer: To automatically select and tune the best ML algorithm for a dataset
AutoML automates the process of selecting the best algorithm and hyperparameters for a given dataset, reducing the need for manual experimentation.