Будь ласка, використовуйте цей ідентифікатор, щоб цитувати або посилатися на цей матеріал: http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/3241
Назва: Data science: opportunities to transform education
Автори: Volkova, Nataliia P.
Rizun, Nina O.
Nehrey, Maryna V.
Ключові слова: data science
high education
clustering
natural language processing
text mining
Дата публікації: 9-вер-2019
Видавництво: Arnold E. Kiv, Vladimir N. Soloviev
Бібліографічний опис: Volkova N. P. Data science: opportunities to transform education [Electronic resource] / Nataliia P. Volkova, Nina O. Rizun, Maryna V. Nehrey // Cloud Technologies in Education : Proceedings of the 6th Workshop on Cloud Technologies in Education (CTE 2018), Kryvyi Rih, Ukraine, December 21, 2018 / Edited by : Arnold E. Kiv, Vladimir N. Soloviev. – P. 48-73. – (CEUR Workshop Proceedings (CEUR-WS.org), Vol. 2433). – Access mode : http://ceur-ws.org/Vol-2433/paper03.pdf
Короткий огляд (реферат): The article concerns the issue of data science tools implementation, including the text mining and natural language processing algorithms for increasing the value of high education for development modern and technologically flexible society. Data science is the field of study that involves tools, algorithms, and knowledge of math and statistics to discover knowledge from the raw data. Data science is developing fast and penetrating all spheres of life. More people understand the importance of the science of data and the need for implementation in everyday life. Data science is used in business for business analytics and production, in sales for offerings and, for sales forecasting, in marketing for customizing customers, and recommendations on purchasing, digital marketing, in banking and insurance for risk assessment, fraud detection, scoring, and in medicine for disease forecasting, process automation and patient health monitoring, in tourism in the field of price analysis, flight safety, opinion mining etc. However, data science applications in education have been relatively limited, and many opportunities for advancing the fields still unexplored.
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URI (Уніфікований ідентифікатор ресурсу): http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/3241
https://doi.org/10.31812/123456789/3241
ISSN: 1613-0073
Розташовується у зібраннях:Кафедра інформатики та прикладної математики

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