Linear regression with multiple variables is also known as “multivariate linear regression”.
We now introduce notation for equations where we can have any number of input variables.
The multivariable form of the hypothesis function accommodating these multiple features is as follows:
Using the definition of matrix multiplication, our multivariable hypothesis function can be concisely represented as:
This is a vectorization of our hypothesis function for one training example; see the lessons on vectorization to learn more.