Summary

In this chapter, we saw how to develop a neural network model that helps to solve a classification type of problem. We started with a simple classification model and explored how to change the number of hidden layers and the number of units in the hidden layers. The idea behind exploring and fine-tuning a classification model was to illustrate how to explore and improve the performance of the classification model. We also saw how to dig deeper to understand the performance of a classification model with the help of a confusion matrix. We purposefully looked at a relatively smaller neural network model at the beginning of this chapter and finished with an example of a relatively deeper neural network model. Deeper networks involving several hidden layers can also lead to overfitting problems, where a classification model may have excellent performance with training data...