The field of study that focuses on the interactions between human language and computers is called Natural Language Processing, or NLP for short. It sits at the intersection of computer science, artificial intelligence, and computational linguistics
Natural Language Processing, usually shortened as NLP, is a branch of artificial intelligence that deals with the interaction between computers and humans using the natural language. The ultimate objective of NLP is to read, decipher, understand, and make sense of the human languages in a manner that is valuable. Most NLP techniques rely on machine learning to derive meaning from human languages.
Natural language processing (NLP) is a field of artificial intelligence in which computers analyze, understand, and derive meaning from human language in a smart and useful way. By utilizing NLP, developers can organize and structure knowledge to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation.
NLP algorithms have a variety of uses. Basically, they allow developers to create a software that understands human language. Due to the complicated nature of human language, NLP can be difficult to learn and implement correctly. However, with the knowledge gained from this article, you will be better equipped to use NLP successfully. Some of the projects developers can use NLP algorithms for are:
- Summarize blocks of text using Summarizer to extract the most important and central ideas while ignoring irrelevant information.
- Create a chat bot using Parsey McParseface, a language parsing deep learning model made by Google that uses Point-of-Speech tagging.
- Automatically generate keyword tags from content using AutoTag, which leverages LDA, a technique that discovers topics contained within a body of text.
- Identify the type of entity extracted, such as it being a person, place, or organization using Named Entity Recognition.
- Use Sentiment Analysis to identify the sentiment of a string of text, from very negative to neutral to very positive.
