Random Forest-Based Retail Management To Improve The Recognition Rates Of Employees

In this paper, we use residual neural network to improve the recognition rates of employees in retail industry sectors. Utilizing data analytics techniques for the goal of analyzing enormous volumes of data to improve retail procedures by acquiring a better grasp of the resulting competences in the market. By adopting information management with the primary objective of doing predictive analysis, an increasing number of businesses are beginning to better anticipate the future wants and needs of their customers. This is being accomplished using data analytics. Using this new strategy, companies will be better able to predict the expectations that their consumers will have, and they will be able to give a strategic response that is both hands-on and practical in response to those requests. This study can be conducted with the support of human resource management, which will conduct both an internal and an external assessment. The proposed method is achieving more accuracy 95 percentage than other existing methods.