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Principles and Applications of Data Science



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Autore: Liu Chuan-Ming Visualizza persona
Titolo: Principles and Applications of Data Science Visualizza cluster
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  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910580211103321
Lo trovi qui: Univ. Federico II
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