In this example, we will work on a regression problem involving more than one variable.
This will be based on a 1993 dataset of a study of different prices among some suburbs of Boston. It originally contained 13 variables and the mean price of the properties there.
The only change in the file from the original one is the removal of one variable
(b), which racially profiled the different suburbs.
Apart from that, we will choose a handful of variables that we consider have good conditions to be modeled by a linear function.
This section contains a list of useful libraries that we will be using in this example and in some parts of the rest of the book, outside TensorFlow, to assist ...