Now that we've defined our problem, our inputs, our desired output, and our cost function, we can quickly code the rest in Keras. The only thing we're missing is a network architecture. We will talk more about that soon. One of my favorite things about Keras is how easy it is tune the network architecture. As you're about to see, it might take a lot of experimentation before you locate the best architecture. If that's true, a framework that easily changes makes your job easier!
Building a binary classifier in Keras
The input layer
As before, our input layer needs to know the dimensions of our dataset. I like to build the entire Keras model inside a function, and allow that function to pass back the compiled...