HOTSPOT (Drag and Drop is not supported)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:
Answer(s): A
HOTSPOT (Drag and Drop is not supported)Select the answer that correctly completes the sentence.Hot Area:
Box 1: NumericFor regression problems, the label column must contain numeric data that represents the response variable.Ideally the numeric data represents a continuous scale.
https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/train-model
You need to create a clustering model and evaluate the model by using Azure Machine Learning designer.What should you do?
Understand steps for clusteringYou 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.
https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/train-clustering- model
You need to track multiple versions of a model that was trained by using Azure Machine Learning.What should you do?
Answer(s): B
Register and track machine learning modelsWith model registration, you can store and version your models in the Azure cloud, in your workspace. The model registry makes it easy to organize and keep track of your trained models.
https://learn.microsoft.com/en-us/azure/machine-learning/concept-model-management-and- deployment
You need to identify groups of rows with similar numeric values in a dataset.Which type of machine learning should you use?
Clustering is an unsupervised machine learning technique used to group similar entities based on their features. Learn how to create clustering models using Azure Machine Learning designer.Scenarios for clustering machine learning modelsClustering machine learning models are used in many industries. A few scenarios are:Cluster customer attribute data into segments for marketing analysis.Cluster geographic coordinates into regions of high traffic in a city for a ride-share application.Cluster written feedback into topics to prioritize customer service changes.
https://learn.microsoft.com/en-us/training/modules/create-clustering-model-azure-machine-learning- designer/2-clustering-scenarios
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