In this chapter, we have learned about neural networks along with their working, and were introduced to backward propagation and the activation function. We studied network initialization and how can we initialize the different types of models. We learned about overfitting and dropouts in the neural network scenario.
We introduced the concept of RNN, and studied a use case regarding the Google stock price dataset. In the next chapter, we will study time series analysis.