Recurrent Neural Networks (RNNs)
In the last section, we learned how we can use CNNs for computer vision tasks such as classifying images. With deep learning, computers are now capable of achieving and sometimes surpassing human performance. Another field that is attracting a lot of interest from researchers is natural language processing. This is a field where RNNs excel.
In the last few years, we have seen a lot of different applications of RNN technology, such as speech recognition, chatbots, and text translation applications. But RNNs are also quite performant in predicting time series patterns, something that's used for forecasting stock markets.
RNN Layers
The common point with all the applications mentioned earlier is that the inputs are sequential. There is a time component with the input. For instance, a sentence is a sequence of words, and the order of words matters; stock market data consists of a sequence of dates with corresponding stock prices.
To accommodate...
