Microsoft Microsoft Certifications AI-900 Questions & Answers

• Question 101:

  HOTSPOT

  To complete the sentence, select the appropriate option in the answer area.

  Hot Area:

  

  Correct Answer:

  

  To perform real-time inferencing, you must deploy a pipeline as a real-time endpoint. Real-time endpoints must be deployed to an Azure Kubernetes Service cluster.

  Reference: https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer#deploy

• Question 102:

  HOTSPOT

  To complete the sentence, select the appropriate option in the answer area.

  Hot Area:

  

  Correct Answer:

  

  In the most basic sense, regression refers to prediction of a numeric target.

  Linear regression attempts to establish a linear relationship between one or more independent variables and a numeric outcome, or dependent variable.

  You use this module to define a linear regression method, and then train a model using a labeled dataset. The trained model can then be used to make predictions.

  Incorrect Answers:

  1.

  Classification is a machine learning method that uses data to determine the category, type, or class of an item or row of data.

  2.

  Clustering, in machine learning, is a method of grouping data points into similar clusters. It is also called segmentation.

  Over the years, many clustering algorithms have been developed. Almost all clustering algorithms use the features of individual items to find similar items. For example, you might apply clustering to find similar people by demographics. You might use clustering with text analysis to group sentences with similar topics or sentiment.

  Reference: https://docs.microsoft.com/en-us/azure/machine-learning/algorithm-module-reference/linear-regression https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/machine-learning-initialize-model-clustering

• Question 103:

  HOTSPOT

  To complete the sentence, select the appropriate option in the answer area.

  Hot Area:

  

  Correct Answer:

  

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

• Question 104:

  HOTSPOT

  To complete the sentence, select the appropriate option in the answer area.

  Hot Area:

  

  Correct Answer:

  

  Reliability and safety: To build trust, it's critical that AI systems operate reliably, safely, and consistently under normal circumstances and in unexpected conditions. These systems should be able to operate as they were originally designed, respond safely to unanticipated conditions, and resist harmful manipulation.

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

• Question 105:

  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 106:

  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:

  

  Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/anomaly-detection

• Question 107:

  You need to reduce the load on telephone operators by implementing a chatbot to answer simple questions with predefined answers. Which two AI services should you use to achieve the goal? Each correct answers presents part of the solution. NOTE: Each correct selection is worth one point.

  A. Azure Machine Learning

  B. Azure Bot Service

  C. Language Service

  D. Translator

  Correct Answer: AB

• Question 108:

  You have a dataset that contains the columns shown in the following table.

  

  You have a machine learning model that predicts the value of ColumnE based on the other numeric columns. Which type of model is this?

  A. analysis

  B. clustering

  C. clustering

  Correct Answer: C

  Regression is a supervised machine learning technique used to predict numeric values.

  Reference: https://learn.microsoft.com/en-us/training/modules/create-regression-model-azure-machine-learning-designer/

• Question 109:

  You need to create a clustering model and evaluate the model by using Azure Machine Learning designer. What should you do?

  A. Split the original dataset into a dataset for training and a dataset for testing. Use the testing dataset for evaluation.

  B. Use the original dataset for training and evaluation.

  C. Split the original dataset into a dataset for features and a dataset for labels. Use the features dataset for evaluation.

  D. Split the original dataset into a dataset for training and a dataset for testing. Use the training dataset for evaluation.

  Correct Answer: A

  Understand steps for clustering

  You can think of the steps to train and evaluate a clustering machine learning model as:

  1.

  Prepare data: Identify the features and label in a dataset. Pre-process, or clean and transform, the data as needed.

  2.

  Train model: Split the data into two groups, a training and a validation set. Train a machine learning model using the training data set. Test the machine learning model for performance using the validation data set.

  3.

  Evaluate performance.

  4.

  Deploy a predictive service: After you train a machine learning model, you need to convert the training pipeline into a real-time inference pipeline. Then you can deploy the model as an application on a server or device so that others can use it.

  Reference: https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/train-clustering-model

• Question 110:

  Which machine learning technique can be used for anomaly detection?

  A. A machine learning technique that classifies objects based on user supplied images.

  B. A machine learning technique that understands written and spoken language.

  C. A machine learning technique that classifies images based on their contents.

  D. A machine learning technique that analyzes data over time and identifies unusual changes.

  Correct Answer: D

  Anomaly Detector, an AI service that helps you foresee problems before they occur.

  Easily embed time-series anomaly detection capabilities into your apps to help users identify problems quickly. Anomaly Detector ingests time-series data of all types and selects the best anomaly detection algorithm for your data to ensure

  high accuracy. Detect spikes, dips, deviations from cyclic patterns, and trend changes through both univariate and multivariate APIs. Customize the service to detect any level of anomaly. Deploy the anomaly detection service where you need

  it — in the cloud or at the intelligent edge.

  Reference: https://azure.microsoft.com/en-us/products/cognitive-services/anomaly-detector