TY  - GEN
N2  - This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.
DO  - 10.1007/978-3-030-59338-4
DO  - doi
AB  - This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.
T1  - Machine learning and big data analytics paradigms :analysis, applications and challenges /
DA  - 2021.
CY  - Cham :
AU  - Hassanien, Aboul Ella,
AU  - Darwish, Ashraf,
VL  - v. 77
CN  - Q325.5
PB  - Springer,
PP  - Cham :
PY  - 2021.
ID  - 1432944
KW  - Machine learning.
KW  - Big data.
KW  - Apprentissage automatique.
KW  - Données volumineuses.
SN  - 9783030593384
SN  - 303059338X
TI  - Machine learning and big data analytics paradigms :analysis, applications and challenges /
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-59338-4
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-59338-4
ER  -