FEATURES OF FRONT-END IMPLEMENTATION FOR MACHINE LEARNING APPLICATIONS

This article is dedicated to modern approaches in front-end development integrated with machine learning models for document recognition tasks. Key aspects of building the user interface are considered, including the organization of file upload and preprocessing processes, visualization of classification results and extracted textual information, as well as ensuring interactive interaction with the model. A technical analysis of the features of integrating the client side with machine learning APIs is provided, including optimization of requests, asynchronous processing, and display of intermediate states. Special attention is given to usability challenges related to the uncertainty of AI responses and the need for user validation of results. In conclusion, the significance of front-end development as an intermediary between the user and a complex intelligent system is highlighted, which determines its role in the successful practical implementation of machine learning-based solutions.