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Alright, let's start with the basics. **Lasso Regression** (Least Absolute Shrinkage and Selection Operator) is a type of linear regression. But wait, what's linear regression? Basically, it's a way to model the relationship between a bunch of variables (like the size of a house, the number of bedrooms, and its price) by finding a straight line (or a plane in higher dimensions) that best fits the data. The goal is to predict the value of a target variable (like the house price) based on one or more predictor variables (like the house size and number of bedrooms). Simple, right?
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