Principles and Applications of Data Science

• Autore: Liu Chuan-Ming
• Pubblicazione: Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
• Descrizione fisica: 1 electronic resource (168 p.)
• Soggetto topico: Technology: general issues; History of engineering & technology
• Soggetto non controllato: deep learning; user preference learning; feature fusion; similar user recommendation; convolutional neural network; image classification; electronic health records; fair exchange; forward secrecy; raw material; mining; terminology; dictionary; terminology application; mobile application; digitization; lexical data; corpus data; linguistic linked open data; neuro-fuzzy; prediction model; air pollution; PM2.5; PM10; self-attention mechanism; graph neural network; data mining; behaviour sequence pattern; behaviour network; water crystal; fine-tuning; supervised; classification; combined classification model; deep transfer learning; focal-segmental; kidney disease; kidney glomeruli; medical image; sclerosed glomeruli; predictive analytics; Internet of Things; peasant farming; smart farming system; crop production prediction
• Persona (resp. second.): LiuChuan-Ming
• Sommario/riassunto: Data science is an emerging multidisciplinary field which lies at the intersection of computer science, statistics, and mathematics, with different applications and related to data mining, deep learning, and big data. This Special Issue on “Principles and Applications of Data Science” focuses on the latest developments in the theories, techniques, and applications of data science. The topics include data cleansing, data mining, machine learning, deep learning, and the applications of medical and healthcare, as well as social media.
• Titolo autorizzato: Principles and Applications of Data Science
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910580211103321
• Lo trovi qui: Univ. Federico II