Microsoft Azure AI Fundamentals 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 flashcards as text
What is the role of a 'validation dataset' during model training?
Answer: To tune hyperparameters and monitor for overfitting during training
The validation dataset is used during training to tune hyperparameters and detect overfitting, while remaining separate from the final test set.
Azure Personalizer uses which type of machine learning to deliver personalized content recommendations?
Answer: Reinforcement learning
Azure Personalizer uses reinforcement learning, where it learns which actions (content selections) yield the best rewards (user engagement) over time.
Which feature of Azure Computer Vision can describe the content of an image in natural language?
Answer: Image captioning / Describe Image
The 'Describe Image' feature in Azure Computer Vision generates a human-readable sentence describing the content and context of an image.
What is the key difference between 'precision' and 'recall' in a classification model?
Answer: Precision measures how many predicted positives are correct; recall measures how many actual positives were found
Precision = true positives / (true positives + false positives); Recall = true positives / (true positives + false negatives) — they measure different error trade-offs.
Which Azure service allows you to build a question-answering system from existing documents and FAQs without training a custom model from scratch?
Answer: Azure Language Service (Question Answering)
The Question Answering feature in Azure Language Service (formerly QnA Maker) extracts Q&A pairs from documents and FAQs to create a searchable knowledge base.
In the context of natural language processing, what is 'tokenization'?
Answer: Breaking text into individual words or subword units for processing
Tokenization splits raw text into smaller units (tokens) such as words or subwords, which are the fundamental inputs that NLP models process.
What does 'confidence score' represent when returned by an Azure Cognitive Services prediction?
Answer: The model's estimated probability that its prediction is correct
A confidence score (typically 0–1 or 0–100%) indicates how certain the model is about its prediction — higher scores mean the model is more confident.