Objective 2.0

Describe fundamental principles of machine learning on Azure

AI-900 Practice Questions

Use this page to practise Describe fundamental principles of machine learning on Azure questions for this certification. Focus on how the exam tests describe fundamental principles of machine learning on azure in scenario format — understanding the why behind each answer builds more durable knowledge than memorising options.

Full Practice Test →All Objectives

What this objective tests

AI-900 Describe fundamental principles of machine learning on Azure — Key Topics

Describe fundamental principles of machine learning on Azure questions on this certification test your ability to deploy and manage describe fundamental principles of machine learning on azure concepts in scenario-based situations.

Core Describe fundamental principles of machine learning on Azure concepts and how they apply in real-world cloud scenarios.
How to deploy describe fundamental principles of machine learning on azure correctly and verify the outcome.
Troubleshooting describe fundamental principles of machine learning on azure issues by interpreting error output and system state.
Cloud best practices and Describe fundamental principles of machine learning on Azure design trade-offs tested by this certification.

Common exam traps

Where candidates lose marks on Describe fundamental principles of machine learning on Azure

⚠Selecting the most expensive service when a simpler managed option meets the requirement.
⚠Forgetting that cloud resources must be explicitly secured — defaults are rarely secure.
⚠Choosing a global service fix when the issue is region-specific.
⚠Overlooking cost implications of cross-region data transfer in architecture questions.

AI-900 Describe fundamental principles of machine learning on Azure — Practice Questions

30 questions from this objective

Question 2mediummultiple choice

Describe fundamental principles of machine learning on Azure

AI-900 Describe fundamental principles of machine learning on Azure — Key Topics

Where candidates lose marks on Describe fundamental principles of machine learning on Azure

AI-900 Describe fundamental principles of machine learning on Azure — Practice Questions

A data scientist wants to train a machine learning model to predict the exact market price of a house based on features such as square footage, number of bedrooms, and location. Which type of machine learning task should be used?

A hospital has a dataset with historical patient records, each labeled as either 'readmitted within 30 days' or 'not readmitted'. The hospital wants to train a model to predict which current patients are likely to be readmitted. Which type of machine learning task is this?

A data scientist trains a machine learning model to predict housing prices. On the training data, the model achieves an R-squared value of 0.99, but on a separate validation dataset it achieves an R-squared of only 0.65. What is the most likely issue with this model?

A data scientist trains a machine learning model on a dataset of housing prices. The model achieves 98% accuracy on the training data but only 72% accuracy on a separate test set. What is the most likely problem with this model?

A data scientist trains a regression model on a dataset with 100 features and 10,000 samples. The model achieves a low training error but a much higher error on a held-out test set. Which approach is most likely to improve the model's generalization performance?

A data scientist trains a regression model to predict house prices. The model has a mean absolute error (MAE) of $5,000 on the test set. Which statement best interprets this metric?

A data scientist trains a classification model to distinguish between images of cats and dogs. The model achieves 99% accuracy on the training set but only 75% accuracy on a validation set. Which concept best describes this situation?

A data scientist is building a model to predict the exact temperature in degrees Celsius based on humidity and atmospheric pressure. The model will output a single numeric value for each input. Which type of machine learning task is this?

A media company wants to automatically organize a large collection of news articles into several topic-based categories (e.g., politics, sports, technology) without using any predefined labels. They plan to use Azure Machine Learning. Which type of machine learning task should they use?

A retail company wants to segment its customers into different groups based on purchasing behavior, without using predefined categories. Which type of machine learning task should they use?

A data scientist trains a deep neural network on a small dataset. The model achieves 100% accuracy on the training data but only 60% accuracy on a validation set. Which technique is most appropriate to address this issue?

A manufacturing team wants to predict product defects based on sensor readings from the production line. They have 10,000 historical samples, each labeled as 'defective' or 'non-defective'. Which type of machine learning should they use in Azure Machine Learning?

A data scientist trains a classification model to predict whether an email is 'phishing' or 'legitimate'. The model achieves 99% accuracy on the training data but only 68% accuracy on the test data. Which action is most likely to help improve the model's generalization performance?

A retail company has a dataset of customer transaction records with no predefined categories. They want to identify natural groupings of customers based on their purchasing behavior to create targeted marketing campaigns. Which type of machine learning should they use in Azure Machine Learning?

A data scientist has a dataset containing thousands of labeled images of cats and dogs. The data scientist wants to train a model that can automatically classify new unlabeled images as either 'cat' or 'dog'. Which type of machine learning should the data scientist use?

All AI-900 Objectives

Describe fundamental principles of machine learning on Azure

AI-900 Describe fundamental principles of machine learning on Azure — Key Topics

Where candidates lose marks on Describe fundamental principles of machine learning on Azure

AI-900 Describe fundamental principles of machine learning on Azure — Practice Questions

A data scientist wants to train a machine learning model to predict the exact market price of a house based on features such as square footage, number of bedrooms, and location. Which type of machine learning task should be used?

A hospital has a dataset with historical patient records, each labeled as either 'readmitted within 30 days' or 'not readmitted'. The hospital wants to train a model to predict which current patients are likely to be readmitted. Which type of machine learning task is this?

A data scientist trains a machine learning model to predict housing prices. On the training data, the model achieves an R-squared value of 0.99, but on a separate validation dataset it achieves an R-squared of only 0.65. What is the most likely issue with this model?

A data scientist trains a machine learning model on a dataset of housing prices. The model achieves 98% accuracy on the training data but only 72% accuracy on a separate test set. What is the most likely problem with this model?

A data scientist trains a regression model on a dataset with 100 features and 10,000 samples. The model achieves a low training error but a much higher error on a held-out test set. Which approach is most likely to improve the model's generalization performance?

A data scientist trains a regression model to predict house prices. The model has a mean absolute error (MAE) of $5,000 on the test set. Which statement best interprets this metric?

A data scientist trains a classification model to distinguish between images of cats and dogs. The model achieves 99% accuracy on the training set but only 75% accuracy on a validation set. Which concept best describes this situation?

A data scientist is building a model to predict the exact temperature in degrees Celsius based on humidity and atmospheric pressure. The model will output a single numeric value for each input. Which type of machine learning task is this?

A media company wants to automatically organize a large collection of news articles into several topic-based categories (e.g., politics, sports, technology) without using any predefined labels. They plan to use Azure Machine Learning. Which type of machine learning task should they use?

A retail company wants to segment its customers into different groups based on purchasing behavior, without using predefined categories. Which type of machine learning task should they use?

A data scientist trains a deep neural network on a small dataset. The model achieves 100% accuracy on the training data but only 60% accuracy on a validation set. Which technique is most appropriate to address this issue?

A manufacturing team wants to predict product defects based on sensor readings from the production line. They have 10,000 historical samples, each labeled as 'defective' or 'non-defective'. Which type of machine learning should they use in Azure Machine Learning?

A data scientist trains a classification model to predict whether an email is 'phishing' or 'legitimate'. The model achieves 99% accuracy on the training data but only 68% accuracy on the test data. Which action is most likely to help improve the model's generalization performance?

A retail company has a dataset of customer transaction records with no predefined categories. They want to identify natural groupings of customers based on their purchasing behavior to create targeted marketing campaigns. Which type of machine learning should they use in Azure Machine Learning?

A data scientist has a dataset containing thousands of labeled images of cats and dogs. The data scientist wants to train a model that can automatically classify new unlabeled images as either 'cat' or 'dog'. Which type of machine learning should the data scientist use?

All AI-900 Objectives