When training and testing a neural net, it’s important to separate training data from validation, so that you aren’t checking the accuracy of the model with the same data that you use to train it. This will help reduce overfitting. We’ll use the validation_split
parameter when fitting our model to automatically split data up into a training set and a validation set, and use that to check the validation accuracy of our model.