Correct Answer: To evaluate how well the trained model performs on new, unseen data
The testing/validation dataset is held back during the training phase. Once the model is trained, it is tested against this unseen data. This proves whether the model has actually ...
Correct Answer
To evaluate how well the trained model performs on new, unseen data
Why This Answer Is Correct
The testing/validation dataset is held back during the training phase. Once the model is trained, it is tested against this unseen data. This proves whether the model has actually learned the underlying patterns (generalization) rather than just memorizing the training data (overfitting).
This question evaluates your knowledge of Machine Learning Principles — a core concept tested in Microsoft Certified: Azure AI Fundamentals (AI-900). Understanding Machine Learning Principles is essential for designing scalable, secure, and cost-effective cloud architectures. Mastery of this topic will help you answer scenario-based questions confidently on exam day.
You want to predict the exact price a house will sell for based on its square footage, number of bedrooms, and zip code. Which type of machine learning model should you use?
A marketing team wants to group their customer database into distinct segments based on purchasing behavior so they can run targeted ad campaigns. The team does not have pre-labeled categories; they want the AI to find natural groupings. Which type of machine learning is this?
In a classification model predicting whether an email is 'Spam' or 'Not Spam', the model correctly identifies 90 out of 100 total emails. This 90% metric is known as what?