What is natural language processing? How does it work? Where is NLP used in the real world?
Our communications, both verbal and written, carry rich information. Even beyond what we are conveying explicitly, our tone, the selection of words add layers of meaning to the communication. As humans, we can understand these nuances, and often predict behavior using the information. But there is an issue: one person alone can generate hundreds if not thousands of words in a single message or statement. And if we want to scale and analyze hundreds, thousands, or millions of people, the situation quickly becomes unmanageable. What if we used computers to automate this process? After all, computer processes can be scaled easily. Well, it's not that simple. Communications fall under something called unstructured data, and computers are not good at working with unstructured data. The text data generated from conversations, customer support tickets, online reviews, news articles, tweets are examples of unstructured data. It's called unstructured because it doesn't fit into the traditional row and column structure of databases, and it is messy and hard to manipulate. But thanks to advances in the field of artificial intelligence, computers have gotten better at making sense of unstructured data. What Is Natural Language Processing (NLP)? Natural Language Processing or NLP is a subfield of Artificial Intelligence that makes natural languages like English understandable for machines. NLP sits at the intersection of computer science, artificial intelligence, and computational linguistics. It enables computers to study the rules and structure of language, and create intelligent systems(built using machine learning/deep learning algorithms) that can automatically perform repetitive analytical and predictive tasks. One of the main reasons natural language processing is so crucial to businesses is that it can be used to analyze large volumes of text data. Take sentiment analysis, for instance, which uses natural language processing to detect emotions in text. It is one…