Microsoft Microsoft Certifications AI-900 Questions & Answers

• Question 91:

  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:

  

  Box 1: Yes

  Content Moderator is part of Microsoft Cognitive Services allowing businesses to use machine assisted moderation of text, images, and videos that augment human review.

  The text moderation capability now includes a new machine-learning based text classification feature which uses a trained model to identify possible abusive, derogatory or discriminatory language such as slang, abbreviated words, offensive,

  and intentionally misspelled words for review.

  Box 2: No

  Azure's Computer Vision service gives you access to advanced algorithms that process images and return information based on the visual features you're interested in. For example, Computer Vision can determine whether an image contains

  adult content, find specific brands or objects, or find human faces.

  Box 3: Yes

  Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization.

  Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.

  Reference:

  https://azure.microsoft.com/es-es/blog/machine-assisted-text-classification-on-content-moderator-public-preview/

  https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing

• Question 92:

  HOTSPOT

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

  Hot Area:

  

  Correct Answer:

  

  Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization.

  Reference: https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing

• Question 93:

  HOTSPOT

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

  Hot Area:

  

  Correct Answer:

  

  Azure Custom Vision is a cognitive service that lets you build, deploy, and improve your own image classifiers. An image classifier is an AI service that applies labels (which represent classes) to images, according to their visual

  characteristics. Unlike the Computer Vision service, Custom Vision allows you to specify the labels to apply.

  Note: The Custom Vision service uses a machine learning algorithm to apply labels to images. You, the developer, must submit groups of images that feature and lack the characteristics in question. You label the images yourself at the time of

  submission. Then the algorithm trains to this data and calculates its own accuracy by testing itself on those same images. Once the algorithm is trained, you can test, retrain, and eventually use it to classify new images according to the needs

  of your app. You can also export the model itself for offline use.

  Incorrect Answers:

  Computer Vision:

  Azure's Computer Vision service provides developers with access to advanced algorithms that process images and return information based on the visual features you're interested in. For example, Computer Vision can determine whether an

  image contains adult content, find specific brands or objects, or find human faces.

  Reference:

  https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/home

• Question 94:

  HOTSPOT

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

  Hot Area:

  

  Correct Answer:

  

  Reference: https://gallery.azure.ai/Experiment/Student-Loan-Repayment-Rate-Prediction

• Question 95:

  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:

  

  Box 1: Yes

  In machine learning, if you have labeled data, that means your data is marked up, or annotated, to show the target, which is the answer you want your machine learning model to predict.

  In general, data labeling can refer to tasks that include data tagging, annotation, classification, moderation, transcription, or processing.

  Box 2: No

  Box 3: No

  Accuracy is simply the proportion of correctly classified instances. It is usually the first metric you look at when evaluating a classifier. However, when the test data is unbalanced (where most of the instances belong to one of the classes), or

  you are more interested in the performance on either one of the classes, accuracy doesn't really capture the effectiveness of a classifier.

  Reference:

  https://www.cloudfactory.com/data-labeling-guide

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

• Question 96:

  HOTSPOT

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

  Hot Area:

  

  Correct Answer:

  

  In machine learning, if you have labeled data, that means your data is marked up, or annotated, to show the target, which is the answer you want your machine learning model to predict.

  In general, data labeling can refer to tasks that include data tagging, annotation, classification, moderation, transcription, or processing.

  Incorrect Answers:

  Not features: In machine learning and statistics, feature selection is the process of selecting a subset of relevant, useful features to use in building an analytical model. Feature selection helps narrow the field of data to the most valuable

  inputs. Narrowing the field of data helps reduce noise and improve training performance.

  Reference:

  https://www.cloudfactory.com/data-labeling-guide

• Question 97:

  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:

  

  Box 1: Yes

  Automated machine learning, also referred to as automated ML or AutoML, is the process of automating the time consuming, iterative tasks of machine learning model development. It allows data scientists, analysts, and developers to build

  ML models with high scale, efficiency, and productivity all while sustaining model quality.

  Box 2: No

  Box 3: Yes

  During training, Azure Machine Learning creates a number of pipelines in parallel that try different algorithms and parameters for you. The service iterates through ML algorithms paired with feature selections, where each iteration produces a

  model with a training score. The higher the score, the better the model is considered to "fit" your data. It will stop once it hits the exit criteria defined in the experiment.

  Box 4: No

  Apply automated ML when you want Azure Machine Learning to train and tune a model for you using the target metric you specify.

  The label is the column you want to predict.

  Reference:

  https://azure.microsoft.com/en-us/services/machine-learning/automatedml/#features

• Question 98:

  HOTSPOT

  You have the following dataset.

  

  You plan to use the dataset to train a model that will predict the house price categories of houses.

  What are Household Income and House Price Category? To answer, select the appropriate option in the answer area.

  NOTE: Each correct selection is worth one point.

  Hot Area:

  

  Correct Answer:

  

  Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio/interpret-model-results

• Question 99:

  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:

  

  Explanation:

  Box 1: Yes

  Azure Machine Learning designer lets you visually connect datasets and modules on an interactive canvas to create machine learning models.

  Box 2: Yes

  With the designer you can connect the modules to create a pipeline draft.

  As you edit a pipeline in the designer, your progress is saved as a pipeline draft.

  Box 3: No

  Reference:

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

• Question 100:

  HOTSPOT

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

  Hot Area:

  

  Correct Answer:

  

  Accelerate your business processes by automating information extraction. Form Recognizer applies advanced machine learning to accurately extract text, key/value pairs, and tables from documents. With just a few samples, Form Recognizer tailors its understanding to your documents, both on-premises and in the cloud. Turn forms into usable data at a fraction of the time and cost, so you can focus more time acting on the information rather than compiling it.

  Reference: https://azure.microsoft.com/en-us/services/cognitive-services/form-recognizer/