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Annotation
В данной работе было проведено сравнение алгоритмов прогнозирования динамики заболеваемости COVID-19 с использованием различных методов машинного обучения. Работа состоит из сбора и подготовки данных, разработки алгоритмов, разработки метрики для их оценки, валидации моделей и построения прогноза количества заболевших на будущее.
In this work, a comparison of methods for predicting the dynamics of COVID19 morbidity was carried out. The work consists of collecting and preparing data, developing algorithms using machine learning methods, developing metrics to estimate them, validating the models, and constructing a forecast of the number of cases for the future.
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