Microsoft Azure AI Fundamentals Artificial Intelligence 3

Question 1

Which concept describes the ability of an AI system to explain how it reached a particular decision or prediction?

Accepted Answer

Interpretability

Answer

Interpretability (also called explainability) refers to how understandable the reasoning behind an AI model's output is to humans.

Question 2

A retailer wants to predict next month's sales figures based on historical data. Which type of machine learning task is this?

Accepted Answer

Regression

Answer

Regression predicts a continuous numerical value, such as a sales figure, based on input features.

Question 3

What is the role of features in a machine learning model?

Accepted Answer

They are the input variables used to make predictions

Answer

Features are the measurable input variables (columns in a dataset) that a model uses to make predictions.

Question 4

Which responsible AI principle ensures that AI systems do not disadvantage particular groups of people unfairly?

Accepted Answer

Fairness

Answer

The fairness principle requires that AI systems treat all people equitably and do not create or reinforce biased outcomes.

Question 5

In machine learning, what does 'training' a model refer to?

Accepted Answer

Adjusting model parameters to minimize error on a dataset

Answer

Training is the process of iteratively adjusting a model's internal parameters to minimize prediction error on the training dataset.

Microsoft Azure AI Fundamentals Practice Test