Microsoft Azure AI Fundamentals Machine Learning 3

Question 1

Which Azure ML compute target is best suited for running large-scale, distributed training jobs?

Accepted Answer

Azure ML Compute Cluster

Answer

Azure ML Compute Clusters scale out automatically to multiple nodes, making them ideal for distributed, large-scale training workloads.

Question 2

What does 'feature engineering' mean in the context of machine learning?

Accepted Answer

Transforming or creating input variables to improve model performance

Answer

Feature engineering involves creating, transforming, or selecting input variables (features) from raw data to help a model learn patterns more effectively.

Question 3

In Azure AutoML, which task type should you select to predict a continuous numeric value such as house price?

Accepted Answer

Regression

Answer

Regression predicts continuous numeric outputs, making it the correct AutoML task type for scenarios like predicting house prices or temperatures.

Question 4

What is the purpose of a validation dataset during model training?

Accepted Answer

To tune hyperparameters and monitor model performance during training

Answer

A validation dataset is used during training to tune hyperparameters and detect overfitting, while the test set provides the final unbiased evaluation.

Question 5

Which ML concept describes using a model trained on one task as a starting point for a different but related task?

Accepted Answer

Transfer learning

Answer

Transfer learning reuses knowledge from a pretrained model (e.g., ImageNet-trained CNN) and fine-tunes it for a new related task with less data.

Microsoft Azure AI Fundamentals Practice Test

Microsoft Azure AI Fundamentals Practice Test

Microsoft Azure AI Fundamentals Machine Learning 3