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В работе изложена сущность подхода к созданию гибридных рекомендательных систем на основе использования таких технологий построения web-приложений, как Spring Boot и Flask, а также библиотек машинного обучения Tensorflow и Keras. Произведен обзор систем такого типа. Проанализированы подходы цифровой обработки сигнала и их применение в целях подготовки данных к тренировке нейронных сетей. Разработана конкретная программная реализация рекомендательной системы в виде многопользовательского web-приложения.
The study considers the approach to creating a hybrid recommen-dation system on the basis of using web application building technologies such as Spring Boot and Flask, as well as Tensorflow and Keras machine learning libraries. A review of systems of this type is made. The approaches to digital signal processing and their application in order to prepare data for training neural networks are analyzed. A specific software implementation of the recommendation system in the form of a multi-user web application has been developed.
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