This is the second part of a series of Natural Language Processing tutorials for beginners. For an introduction to NLP, please check out the first part.
Introduction:
Let me tell you a story.
Tim is a little guy who likes to build things with his varied Lego© pieces. However, Tim is a bit messy, so he keeps all the components of his different puzzles in a big drawer. He now wants to build a castle with some Lego© pieces but, in order to do that (since he is very meticulous with his artworks), he first selects the pieces that could be useful from the entire set by selecting only Lego© pieces. Then, he removes the damaged pieces and the ones that he does not find useful for his purpose, and unifies some small ones that could fit together in a block. Later, he groups pieces by their colour, shape or purpose. Shortly after, Tim brings all the pieces together in a specific order and builds his mighty castle. Finally, he can play with it.
In this post we will see that, when we try to approach an NLP task (and also most of Machine Learning ones), we should behave like Tim.
