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3 cards from this section. Quick, good the night before a test.
Define regression in your own words.
Think about how you would explain it to someone unfamiliar with statistics.
Give an example of where regression might be used.
Consider daily activities where you make predictions based on available information.
What is regression used for in machine learning?
Consider what kind of outcomes you are trying to predict with regression.
True or False: Regression can be used to categorize data into groups.
Think about the difference between predicting a score versus assigning a label.
A dataset contains information on car prices based on features such as brand, mileage, and age. You are tasked with predicting the price of a new model. Discuss how you would approach building a regression model for this dataset.
Consider variables that might influence car prices the most.
Classify the following scenarios as regression or classification: a) predicting the height of a child based on their age, b) determining if an email is spam or not.
Think about whether the outcome is a number or a category.
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