Active learning to minimize the possible risk of future epidemics /

Active learning to minimize the possible risk of future epidemics / KC Santosh, Suprim Nakarmi.

Future epidemics are inevitable, and it takes months and even years to collect fully annotated data. The sheer magnitude of data required for machine learning algorithms, spanning both shallow and deep structures, raises a fundamental question: how big data is big enough to effectively tackle future...

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Bibliographic Details
Online Access: Full Text (via Springer)
Main Authors: Santosh, K. C. (Author), Nakarmi, Suprim (Author)
Format: Electronic eBook
Language:English
Published: Singapore : Springer, [2023]
Series:SpringerBriefs in applied sciences and technology.
SpringerBriefs in applied sciences and technology. Computational intelligence.
Subjects:
Machine learning.
Machine learning > Case studies.
Data mining.
Data mining > Case studies.
Epidemiology > Data processing.
Epidemiology > Data processing > Case studies.

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Call Number: RA652.2.D38
RA652.2.D38 Available

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