Binary classification problems

In this exercise, you will again make use of credit card data. The target variable, default, indicates whether a credit card holder defaults on his or her payment in the following period. Since there are only two options--default or not--this is a binary classification problem. While the dataset has many features, you will focus on just three: the size of the three latest credit card bills. Finally, you will compute predictions from your untrained network, outputs, and compare those the target variable, default.

The tensor of features has been loaded and is available as bill_amounts. Additionally, the constant(), float32, and keras.layers.Dense() operations are available.

Define inputs as a 32-bit floating point constant tensor using bill_amounts.
Set dense1 to be a dense layer with 3 output nodes and a relu activation function.
Set dense2 to be a dense layer with 2 output nodes and a relu activation function.
Set the output layer to be a dense layer with a single output node and a sigmoid activation function.

Exercise

Binary classification problems

Instructions