The latest Microsoft AI-900 Azure AI Fundamentals certification actual real practice exam question and answer (Q&A) dumps are available free, which are helpful for you to pass the Microsoft AI-900 Azure AI Fundamentals exam and earn Microsoft AI-900 Azure AI Fundamentals certification.
Table of Contents
Question 621
You created a classification model. Below is the confusion matrix for this model:
What is the name of the metric that uses TP/(TP+FN) expression for its value calculation?
Answer
Recall
Explanation
The confusion matrix (or error matrix) provides a tabulated view of predicted and actual values for each class. It is usually used as a performance assessment for classification models.
A binary confusion matrix is divided into four squares that represent the following values:
- True positive (TP) – the number of positive cases that the model predicted right.
- True negative (TN) – the number of negative cases that the model predicted right.
- False positive (FP) – the number of positive cases that the model falsely predicted right.
- False negative (FN) – the number of negative cases that the model falsely predicted right.
Recall metric defines how many positive cases that the model predicted are actually predicted right. We can calculate this metric using the following formula: TP/(TP+FN).
Accuracy is incorrect: a formula for Accuracy metric calculation is (TP+TN)/Total number of cases.
Precision is incorrect: a formula for Precision metric calculation is TP/(TP+FP).
F1 Score is incorrect: a formula for F1 metric calculation is 2TP/(2TP+FP+FN).
Selectivity is incorrect: this expression is for Selectivity (or true negative rate) metric calculation: TN/(TN+FP).
Question 622
You install a Visual product search application on your mobile. The application searches products based on the images that you capture by mobile camera.
What Computer Vision common task this application uses for the product search?
Answer
Image Classification
Explanation
You use your camera to capture a picture of the product. An application identifies this product utilizing the Image classification model and submits it for a search.
The Image classification model helps to classify images based on their content.
Object detection is incorrect because the Object detection model helps to identify objects and their boundaries within the image.
Semantic segmentation is incorrect because the Semantic segmentation model helps classify pixels to the objects they belong to.
Face detection is incorrect because Face detection is a Computer vision technique that helps detect and recognize people’s faces.
Image Analysis is incorrect because Image Analysis helps extract information from the images, tag them, and create a descriptive image summary.
Question 623
You need to train and test your model. You prepared data for model training. You decided to use all the data for model training and then for the model validation.
Does this decision help you to achieve your goal?
Answer
No
Explanation
You have to split your data into two sets: the first is for model training and the second for model testing. If you are using Automated machine learning, it automatically does that for you as part of data preparation and model training.
Question 624
You created a Personal Virtual Assistant.
Select all responsible AI principles that your solution must follow.
Answer
Inclusiveness, Reliability and Safety, Privacy and Security
Explanation
Microsoft recognizes six principles of responsible AI: Fairness, Reliability and safety, Privacy and security, Transparency, Inclusiveness and Accountability.
Therefore all other options are incorrect.
Question 625
You want to create a model to predict sales of ice cream based on historic data that includes daily ice cream sales totals and weather measurements. Which Azure service should you use?
Answer
Azure Machine Learning
Question 626
You are designing an AI application that uses images to detect cracks in car windshields and warn drivers when a windshield should be repaired or replaced. What AI workload is described?
Answer
Computer Vision
Question 627
A predictive app provides audio output for visually impaired users. Which principle of Responsible AI is reflected here?
Answer
Inclusiveness
Question 628
In Azure Machine Learning studio, what can you use to author regression machine learning pipelines using a drag-and-drop interface?
Answer
Designer
Question 629
You are creating a training pipeline for a regression model. You use a dataset that has multiple numeric columns in which the values are on different scales. You want to transform the numeric columns so that the values are all on a similar scale. You also want the transformation to scale relative to the minimum and maximum values in each column. Which module should you add to the pipeline?
Answer
Normalize Data
Question 630
Why do you split data into training and validation sets?
Answer
Splitting data into two sets enables you to compare the labels that the model predicts with the actual known labels in the original dataset.