In this recipe, we will use TensorFlow to solve two-dimensional linear regression with the matrix inverse method.
Using the matrix inverse method
Getting ready
Linear regression can be represented as a set of matrix equations, say 
. Here, we are interested in solving the coefficients in matrix x. We have to be careful if our observation matrix (design matrix) A is not square. The solution to solving x can be expressed as 
. To show that this is indeed the case, we will generate two-dimensional data, solve it in TensorFlow, and plot the result.
How to do it...
We proceed...
