Creating predictive models with Keras

Our data now contains the following columns:

amount, 
oldBalanceOrig, 
newBalanceOrig, 
oldBalanceDest, 
newBalanceDest, 
isFraud, 
isFlaggedFraud, 
type_CASH_OUT, 
type_TRANSFER, isNight

Now that we've got the columns, our data is prepared, and we can use it to create a model.

Extracting the target

To train the model, a neural network needs a target. In our case, isFraud is the target, so we have to separate it from the rest of the data. We can do this by running:

y_df = df['isFraud']
x_df = df.drop('isFraud',axis=1)

The first step only returns the isFraud column and assigns it to y_df.

The second step returns all columns except isFraud and assigns them to x_df.

We also need to convert our data from a pandas DataFrame to ...

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