October 2018
Intermediate to advanced
172 pages
4h 6m
English
In its most fundamental form, the expression for the linear regression algorithm can be written as follows:

In the preceding equation, the output of the model is a numeric outcome. In order to obtain this numeric outcome, we require that each input feature be multiplied with a parameter called Parameter1, and we add the second parameter, Parameter2, to this result.
So, in other words, our task is to find the values of the two parameters that can predict the value of the numeric outcome as accurately as possible. In visual terms, consider the following diagram:
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