I don't think there is much to gain from this tutorial, then again it doesn't pretend to offer you much either. For example in the code you are discussing, defining a model as variables and operations, instead of as a function, was confusing to me. Probably Tensorflow overloads the operations, but normally when you read "y = mx + b" you expect y to be computed directly and not to be stored as a model. "f = lambda m, x, b: m x + b" seems much more clear to me.