HOTSPOT - You have an Azure Machine Learning model that predicts product quality. The model has a training dataset that contains 50,000 records. A sample of the data is shown in the following table. 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:
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:
Which two actions are performed during the data ingestion and data preparation stage of an Azure Machine Learning process? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
You need to predict the animal population of an area. Which Azure Machine Learning type should you use?
A. regression
B. clustering
C. classification
Regression is a supervised machine learning technique used to predict numeric values. Reference: https://docs.microsoft.com/en-us/learn/modules/create-regression-model-azure-machine-learning-designer/1-introduction
Question 77
You are processing photos of runners in a race. You need to read the numbers on the runners' shirts to identity the runners in the photos. Which type of computer vision should you use?
A. facial recognition
B. optical character recognition (OCR)
C. semantic segmentation
D. object detection
Optical character recognition (OCR) allows you to extract printed or handwritten text from images and documents. Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview-ocr
Question 78
Which two languages can you use to write custom code for Azure Machine Learning designer? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
A. Python
B. R
C. C#
D. Scala
Use Azure Machine Learning designer for customizing using Python and R code. Reference: https://azure.microsoft.com/en-us/services/machine-learning/designer/#features
Question 79
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:
Box 1: Yes - For regression problems, the label column must contain numeric data that represents the response variable. Ideally the numeric data represents a continuous scale. Box 2: No - K-Means Clustering - Because the K-means algorithm is an unsupervised learning method, a label column is optional. If your data includes a label, you can use the label values to guide selection of the clusters and optimize the model. If your data has no label, the algorithm creates clusters representing possible categories, based solely on the data. Box 3: No - For classification problems, the label column must contain either categorical values or discrete values. Some examples might be a yes/no rating, a disease classification code or name, or an income group. If you pick a noncategorical column, the component will return an error during training. Reference: https://docs.microsoft.com/en-us/azure/machine-learning/component-reference/train-model https://docs.microsoft.com/en-us/azure/machine-learning/component-reference/k-means-clustering
Question 80
Your company wants to build a recycling machine for bottles. The recycling machine must automatically identify bottles of the correct shape and reject all other items. Which type of AI workload should the company use?
A. anomaly detection
B. conversational AI
C. computer vision
D. natural language processing
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. Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview
