1. Explain the goal of linear regression using the equation $y = mx + b$. What do $m$ and $b$ represent?
2. What is the primary difference in the output of a regression model versus a classification model?
3. How does a decision tree make a prediction?
4. Give an example of a business problem that could be solved with classification (e.g., spam detection)
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