Basic neural network overview

At the highest level, a neural network, which solves supervised problems, works as follows:

1. Obtain training data (such as images for image recognition or sentences for generating text)
2. Encode the data (neural networks work with numbers so a numeric representation of the data is required)
3. Build the architecture of your neural network model
4. Train the model until you are satisfied with the results
5. Evaluate your model by making a fresh new prediction

Let's see how these steps are applied for an RNN.