Linear Regression in One Variable

This is a supervised learning algorithm where we estimate the value of a dependent target variable using a linear combination of operations on an independent variable.

It is also called Univariate Linear Regression.

There is one input and one output.

Since it is a form of supervised learning, the end result is already known.

The general hypothesis function is of the form:

hθ(x)=θ0+θ1xh_θ(x) = θ_0 + θ_1x

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