Free AI-900 Exam Braindumps

- (Exam Topic 1)
What are three Microsoft guiding principles for responsible AI? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

1. A. knowledgeability
2. B. decisiveness
3. C. inclusiveness
4. D. fairness
5. E. opinionatedness
6. F. reliability and safety

Correct Answer: CDF
Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles

- (Exam Topic 1)
For a machine learning progress, how should you split data for training and evaluation?

1. A. Use features for training and labels for evaluation.
2. B. Randomly split the data into rows for training and rows for evaluation.
3. C. Use labels for training and features for evaluation.
4. D. Randomly split the data into columns for training and columns for evaluation.

Correct Answer: D
In Azure Machine Learning, the percentage split is the available technique to split the data. In this technique, random data of a given percentage will be split to train and test data.
Reference:
https://www.sqlshack.com/prediction-in-azure-machine-learning/

- (Exam Topic 1)
To complete the sentence, select the appropriate option in the answer area.

Solution:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection

Does this meet the goal?

1. A. Yes
2. B. No

Correct Answer: A

- (Exam Topic 1)
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Solution:
Box 1: No
Box 2: Yes
Box 3: Yes
Anomaly detection encompasses many important tasks in machine learning: Identifying transactions that are potentially fraudulent.
Learning patterns that indicate that a network intrusion has occurred. Finding abnormal clusters of patients.
Checking values entered into a system. Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/anomaly-detection

Does this meet the goal?

1. A. Yes
2. B. No

Correct Answer: A

- (Exam Topic 2)
Which metric can you use to evaluate a classification model?

1. A. true positive rate
2. B. mean absolute error (MAE)
3. C. coefficient of determination (R2)
4. D. root mean squared error (RMSE)

Correct Answer: A
What does a good model look like?
An ROC curve that approaches the top left corner with 100% true positive rate and 0