Microsoft Azure AI Fundamentals

Here you have the best Microsoft AI-900 practice exam questions

  • You have 246 total questions to study from
  • Each page has 5 questions, making a total of 50 pages
  • You can navigate through the pages using the buttons at the bottom
  • This questions were last updated on December 4, 2024
Question 1 of 246

A company employs a team of customer service agents to provide telephone and email support to customers.

The company develops a webchat bot to provide automated answers to common customer queries.

Which business benefit should the company expect as a result of creating the webchat bot solution?

    Correct Answer: B

    The primary business benefit of creating a webchat bot to provide automated answers to common customer queries is a reduced workload for the customer service agents. By handling routine and repetitive questions, the bot frees up the agents to focus on more complex issues, improving efficiency and responsiveness.

Question 2 of 246

For a machine learning progress, how should you split data for training and evaluation?

    Correct Answer: B

    The correct approach to splitting data for training and evaluation in a machine learning process is to randomly divide the data into rows for training and rows for evaluation. This method ensures that both training and evaluation sets are representative of the overall dataset, thus helping to create a more accurate model. Randomly splitting into rows helps in mitigating any bias and ensures that the evaluation of the model's performance is reliable.

Question 3 of 246

HOTSPOT -

You are developing a model to predict events by using classification.

You have a confusion matrix for the model scored on test data as shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.

NOTE: Each correct selection is worth one point.

Hot Area:

    Correct Answer:

    Box 1: 11 -

    TP = True Positive.

    The class labels in the training set can take on only two possible values, which we usually refer to as positive or negative. The positive and negative instances that a classifier predicts correctly are called true positives (TP) and true negatives (TN), respectively. Similarly, the incorrectly classified instances are called false positives (FP) and false negatives (FN).

    Box 2: 1,033 -

    FN = False Negative -

    Reference:

    https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance

Question 4 of 246

You build a machine learning model by using the automated machine learning user interface (UI).

You need to ensure that the model meets the Microsoft transparency principle for responsible AI.

What should you do?

    Correct Answer: B

    To ensure that the machine learning model meets the Microsoft transparency principle for responsible AI, you should enable the 'Explain best model' feature. This option provides insight into the model's decision-making process by generating explanations and highlighting which features are most important in making predictions. This aligns with the transparency principle, as it allows stakeholders to understand and trust the model's outputs, ensuring compliance with ethical and regulatory standards.

Question 5 of 246

HOTSPOT -

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

Hot Area:

    Correct Answer:

    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