Classical models built from the math you already know
Every model in this course, whether it is a straight regression line or a deep decision tree, does exactly the same three things: it takes an input, runs it through some adjustable machinery, and hands back a prediction. Write that machinery as f(x; θ). An input x goes in, a set of adjustable numbers θ (theta) controls how the machine bends that input into an output, and a prediction comes out. Change θ and the model's behaviour changes with it, even though the recipe f itself never does.
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▶ What Makes a Model Learn?