Generative Ai And Deep Learning Applications In Retail Catalog Management

Abstract

In today’s exceedingly competitor and ever changing retail environment,' being able to keep track of and deal large and changing numbers of products is an base problem. The two above mentioned techniques of cataloged direction were ordinarily quite time consuming, uncontrollable and could cause single errors which declaration the power of the commercial to work under force or for large organizations. The following paper discusses the use of Generative AI and Deep Learning to heighten and automated commercialized cataloged handling. Retailers could meliorate crossway classification, gain more detailed data about products, prefer the right prices for products, and use the deep data insights for inventory. This paper also discusses single methods used in the psychoanalysis of the data such as the Convolutions Neural Networks CNN oft used in the psychoanalysis of images as well as Natural Language Processing NLP for text extension and Generative Adversarial Networks GANG for the biosynthetic of fake crossway data. It also explores the effects of these technologies on reproductive workflow, customers’ gratification and concern competitiveness.