Natural Language Processing Techniques Using Machine Learning

Abstract

Natural language processing (NLP) is an
artificial intelligence subset. Computers can
talk in people's native languages, and other
language-related jobs are scaled. NLP enables
computers to read text and hear voices,
comprehend it, measure sentiment, and
identify significant components. NLP is a
synthesis of several disciplines, including
computing linguistics, machine learning, deep
learning, and statistics. These technologies
work together to enable computer software to
interpret and understand human language in
the same way that another human would,
including meaning, intent, and sentiment.
Human language can be understood by
machines. It could take the form of speech or
text. It employs ML (Machine Learning) to
achieve the goal of Artificial Intelligence. The
ultimate goal is to bridge the gap between
how humans communicate and what
computers can understand.
When used in conjunction NLP produces
systems that can learn to complete tasks on
their own and improve with practice using
machine learning techniques. Among many
other things, NLP-powered solutions can
assist you in categorizing and recognizing
identifiable entities from commercial
correspondence or assessing mood in social
media posts. In this study, the importance of
machine learning in NLP and its potential
applications are discussed in detail.