Insightforge | AI & Data Science on Instagram: "In three dimensions, linear regression can be visualized as a plane that best fits the data. When we move into higher dimensions, this idea extends to an n-dimensional hyperplane that represents the model’s predictions. Training this model relies on calculus and linear algebra, along with a way to measure how well the hyperplane matches the data. This measurement is the loss function, most commonly the mean squared error (MSE) or similar variants.