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Linear regression is a method for finding the straight line or hyperplane
that best fits a set of points. This module explores linear regression
intuitively before laying the groundwork for a machine learning approach
to linear regression.
Descending into ML
Learning From Data
There are lots of complex ways to learn from data
But we can start with something simple and familiar
Starting simple will open the door to some broadly useful methods
A Convenient Loss Function for Regression
L2 Loss for a given example is also called squared error
= Square of the difference between prediction and label