Introduction

Text analysis and natural language processing (NLP) is an integral part of modern artificial intelligence systems. Computers are good at understanding rigidly-structured data with limited variety. However, when we deal with unstructured free-form text, things begin to get difficult. Developing NLP applications is challenging because computers have a hard time understanding underlying concepts. There are also many subtle variations to the way in which we communicate things. These can be in the form of dialects, context, slang, and so on.

In order to solve this problem, NLP applications are developed based on machine learning. These algorithms detect patterns in text data so that we can extract insights from it. Artificial intelligence companies make heavy use of NLP and text analysis to deliver relevant results. Some of the most common applications of NLP include search engines, sentiment analysis, topic modeling, part-of-speech tagging, entity recognition, and so on. The goal...