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Data analytics is proving to be an ally for epidemiologists as they
join forces with data scientists to address the scale of crises.
Analytics examined from many sources can derive insights and be
used to study and fight global outbreaks. Pandemic analytics is a
modern way to combat a problem as old as humanity itself: the
proliferation of disease. Machine Learning and Data Analytics for
Predicting, Managing, and Monitoring Disease explores different
types of data and discusses how to prepare data for analysis,
perform simple statistical analyses, create meaningful data
visualizations, predict future trends from data, and more by
applying cutting edge technology such as machine learning and data
analytics in the wake of the COVID-19 pandemic. Covering a range of
topics such as mental health analytics during COVID-19, data
analysis and machine learning using Python, and statistical model
development and deployment, it is ideal for researchers,
academicians, data scientists, technologists, data analysts,
diagnosticians, healthcare professionals, computer scientists, and
students.
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