# What is the normal equation? — An equation that can minimize J(theta), solving for theta, instead of using gradient descent. Also called ordinary least squares (OLS) or linear least squares, it's a method for estimating the unknown parameters in a linear regression model, with the goal of minimizing the sum of the squares of the differences between the observed responses in the given dataset and those predicted by a linear function of a set of explanatory variables.

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