Identify Common Machine Learning Techniques AI-900 Practice Questions (Page 5)

Questions 21–25

1. 21expert · hard

   A company wants to build a system that can identify plant diseases from photos of leaves. The images vary in lighting, angle, and background. They have a large dataset of labeled images. Which approach should they use?

   • AUse a regression model to predict the severity of the disease.
   • BUse a clustering algorithm to group similar leaf images.
   • CTrain a deep convolutional neural network on the labeled images.
   • DUse a transformer to process the images as text descriptions.
   Reveal Solution Discussion Select an answer first
2. 22expert · hard

   A manufacturing company wants to group similar production batches based on quality metrics and sensor readings. They also want to predict the defect rate for each batch. They have historical data with defect rates. Which approach should they use?

   • AUse clustering to identify batch groups, then train a regression model for each group to predict defect rate.
   • BUse classification to assign batches to predefined quality categories.
   • CUse a transformer to generate a text summary of each batch.
   • DUse regression to predict defect rate, then use the residuals to cluster batches.
   Reveal Solution Discussion Select an answer first
4. 23foundation · easy

   Which statement accurately describes a benefit of deep learning over traditional machine learning?

   • AIt can automatically learn relevant features from raw data
   • BIt does not require any computational resources
   • CIt can only be used for classification tasks
   • DIt always requires less training data
   Reveal Solution Discussion Select an answer first
5. 24foundation · easy

   A retail company wants to use machine learning to predict next month's total sales revenue in dollars. Which type of machine learning technique should they use?

   • AAnomaly detection
   • BClassification
   • CClustering
   • DRegression
   Reveal Solution Discussion Select an answer first
6. 25application · medium

   A bank wants to automatically approve or reject loan applications based on applicant data such as income, credit score, and employment history. They have historical data with approved/rejected outcomes. Which technique should they use?

   • ARegression to predict the probability of default.
   • BClustering to group similar applicants.
   • CClassification to assign each application to 'approve' or 'reject'.
   • DA transformer to process the application text.
   Reveal Solution Discussion Select an answer first