Fundamental principles of machine learning on Azure
Practise only this domain. 81 questions with explanations, 20 at a time.
Start this domainSample questions
- Clustering belongs to which learning paradigm?Easy
- Why is a dataset divided into training and test portions?Medium
- Which set of activities describes feature engineering?Medium
- Which activity belongs to the deployment stage of the machine learning lifecycle?Medium
- What does hyperparameter tuning involve?Hard
- Why do data scientists perform feature engineering?Easy
- A model must flag fraudulent card transactions, which are a tiny fraction of all activity. Which evaluation approach suits this problem?Medium
- A production model's accuracy falls over three months even though monitoring shows the input feature distributions have not moved. What is the most likely explanation?Hard
- An Azure Machine Learning designer pipeline imputes missing values with the column mean and must report trustworthy test metrics. Where should the imputation be fitted?Hard
- A deployed endpoint's response time rose from 50 ms to 500 ms. Traffic has grown, yet CPU and GPU utilisation on the serving nodes stays low. What is the most likely cause?Hard
- Which pair of techniques is used to guard against overfitting?Hard