Natural Language Processing (NLP)

What is Natural Language Processing?

Natural language processing (NLP) is a scientific field that’s concerned with writing software that can understand and process “natural” human language. The term “natural language” means ordinary language that humans use to communicate with each other. To put simply, NLP enables computer programs to understand ordinary language like humans do.

An example of NLP is customer service chatbots “talking” to humans using ordinary language to assist customers. We’ll explore many other real-world applications of NLP later in this article.

Chatbot providing customer service is example of real-world application where natural language processing plays a major role.

Chatbot providing customer service is example of real-world application where natural language processing plays a major role.

NLP is a sub-field of linguistics (study of human language), computer science, and machine learning. It has been around for over over half a century, tracing its roots to a paper titled “Computing Machinery and Intelligence” published by Alan Turing in 1950s. We interact with NLP on a daily basis, without even realizing it from virtual assistants (Alexa) to search engines to many business intelligence applications to analyze large amounts of data.

NLP is at the intersection of linguistics, computer science, and machine learning.

NLP is at the intersection of linguistics, computer science, and machine learning.

How does NLP work?

To make computer programs understand normal human languages, NLP relies heavily on machine learning techniques to process the input in a way that computer programs can understand the intention and context.

There are two main parts of NLP: data pre-processing and NLP algorithms.

Data Pre-Processing

Data preprocessing means cleaning up text data and preparing it so that the algorithms can process it. Here are some common pre-processing steps:

  • Tokenization

TODO



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