According to my professor one of the first steps in modelling a NN is to use a powerful enough model.
The first step is to create a model that is powerful enough to achieve very high accuracies (very low loss) on the training data, at least when no regularisation is used.
What are some of the things (obviously apart of regulazing and adjusting learning rate), that I can do to make my model "powerful" enough, in other words to let it overfit on the training data?
Am I looking in the right direction with the following things?
- Add extra layers
- Make layers thicker (more neurons)