Exploration – Machine Learning Fundamental Concepts
Exploration
The “Usage + Quotas” section of the ML workspace shows the dedicated core usage as shown in Figure 3-39.
Figure 3-39Exploring usage + quota
Delete Resources
To avoid any charges, it is critical to delete the resources once the ML model is no longer needed. Figure 3-40 shows Delete button to delete the ML model.
Figure 3-40Deleting the model
Introspective Practice
After you’ve finished reading the chapter, it’s time for you to take a quiz to see how much you remember.
- Clinical measurements will help hospitals predict diabetes risk. How should the hospital use automated machine learning?
a. Classification
b. Regression
c. Time series forecasting
- A real estate marketing research company in the United States wants to predict the price of residential units based on given features such as the location, area of the house in sq. feet, number of bedrooms, etc. Which category of machine learning model should be implemented?
a. Regression
b. Classification
c. Clustering
- You have a full dataset available. Your requirement is to prepare a training and validation subset based on the given dataset randomly. Your dataset consists of features and labels. You have a two-class decision forest module and a training module. You have to score modules and evaluate modules to test the trained model using a validation set. What module should you add to your Azure ML pipeline?
a. Join Data
b. Split Data
c. Select Columns in Dataset
- What are the building blocks available in Azure ML Studio’s drag-and-drop interface for authoring regression machine learning pipelines?
a. Designer
b. Automated ML
c. Notebooks
- You’re training and testing a k-means clustering model with Azure ML. Your model should cluster items into three groups. Which k-means clustering property should you set?
a. Set iterations to 3
b. Set the random number seed to 3
c. Set the number of centroids to 3
