Application of Natural Language Processing (NLP) in Machine Learning
NLP and statistics-based “machine learning” (ML) have demonstrated accomplishment in challenging learning challenges and Automation, self-management technologies, speech synthesis, and deep learning advancements have empowered machines to achieve heretofore unthinkable feats.
Abstract
In recent years, research and development in the domains of artificial intelligence and its related sub - fields, such machine learning, deep learning, and natural language processing, have grown at an unheard-of rate. The availability of powerful operating systems at more affordable prices and the variety of applications available in these research domains are the new sources of enthusiasm. The capability of computer systems to explain human languages is known as natural language processing, and that is a challenging undertaking where various learning techniques have performed a crucial part in correct analysis. The NLP sector is flourishing, and one current debate assessment of professionals estimated that just by 2050, all smart computers will be capable of executing any intellectual work which an individual could accomplish. NLP and statistics-based “machine learning” (ML) have demonstrated accomplishment in challenging learning challenges. Automation, self-management technologies, speech synthesis, and deep learning (DL) advancements have empowered machines to achieve heretofore unthinkable feats. Secondary method of data analysis has been done for this study to collect relevant and statistical information related to research topic. In this article, mathematical expressions and detailed analysis has been conducted.