A Quick Tutorial on NLP Basics
A reference guide for the building blocks of Natural Language Processing
Introduction
Natural Language Processing has been receiving a lot of attention lately, mostly associated with the incredible successes of models like BERT (bidirectional encoder representations), GPT-3, and many others.
In this light, here we will explore the intuitions and fundamental code for understanding the basics of NLP, in order to help you grasp the basic concepts of the field as well as how to implement them in python.
Definition and concepts
Let’s start with a simple definition for what Natural Language Processing is:
It is a subfield of artificial intelligence concerned with teaching machines how to process and analyze data from natural human language.
The ultimate objective of the field is to teach computers how to understand language, in a broad sense.
Usually, any language, be it Mandarin, English, coding, mathematics, or any other, involves the following three components:
- Syntax: rules for ordering words in speech and text.
- Semantics: rules for word meanings and the ways through which these meanings connect.
