Natural Language Generation using Sequence Models

What if I tell you that you can enable your own device to write for you in your own style in under 100 lines of code? The idea to make your device write on your behalf is remarkably inspiring. This practice is referred to as Text Generation or Natural Language Generation, which is a subfield of Natural Language Processing (NLP). The fundamentals of text generation can be easily broken down into a simple supervised machine learning problem, wherein, there exists certain features (called x) with their corresponding labels (called y), and using these we can create our own prediction function which will then generate our predicted labels (called y or yhat). We then map these predicted labels to the actual labels to determine the cost and optimise it using an optimisation algorithm such as Gradient Descent, RMSprop or even the Adam optimiser.