Summary
In this chapter, we discussed image classification modeling. Now, you should be able to explain what a neural network is, as well as forward and backward propagation. You should know the role of loss functions, activation functions, and optimizers in a neural network. Also, you should be able to find your way around loading data from a TensorFlow dataset. Finally, you should be familiar with how to build, compile, fit, and train a neural network for image classification as well as evaluate the model, plot the loss and accuracy curves, and interpret these visualizations.
In the next chapter, we will explore several ideas we can apply to improve our model’s performance.
