A first look at linear regression

This sample shows how a tutorial is written. Replace content/tutorials/linear-regression.mdx with a real lesson.

A simple line is

$$\hat{y} = \beta_0 + \beta_1 x$$

and the slope on its own is $\beta_1$.

def predict(x, intercept, slope):
    return intercept + slope * x

Squared error for one point is $(y - \hat{y})^2$. That is enough to confirm code fences and LaTeX both render.