Data Science for Infectious Disease Data Analytics: An Introduction with R by Lily Wang
Requirements: .PDF reader, 17,2 MB
Overview: Data Science for Infectious Disease Data Analytics: An Introduction with Rprovides an overview of modern data science tools and methods that have been developed specifically to analyze infectious disease data. With a quick start guide to epidemiological data visualization and analysis in R, this book spans the gulf between academia and practices providing many lively, instructive data analysis examples using the most up-to-date data, such as the newly discovered coronavirus disease (COVID-19). The primary emphasis of this book is the data science procedures in epidemiological studies, including data wrangling, visualization, interpretation, predictive modeling, and inference, which is of immense importance due to increasingly diverse and nonexperimental data across a wide range of fields. The knowledge and skills readers gain from this book are also transferable to other areas, such as public health, business analytics, environmental studies, or spatio-temporal data visualization and analysis in general.
Genre: Non-Fiction > Tech & Devices
Download Instructions:
https://drop.download/xde4362v1rgw
https://turbobit.net/f1iftz3mpvzz.html
https://rg.to/file/cdb6f0941425361087a4abbbcdfa7a51
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Requirements: .PDF reader, 17,2 MB
Overview: Data Science for Infectious Disease Data Analytics: An Introduction with Rprovides an overview of modern data science tools and methods that have been developed specifically to analyze infectious disease data. With a quick start guide to epidemiological data visualization and analysis in R, this book spans the gulf between academia and practices providing many lively, instructive data analysis examples using the most up-to-date data, such as the newly discovered coronavirus disease (COVID-19). The primary emphasis of this book is the data science procedures in epidemiological studies, including data wrangling, visualization, interpretation, predictive modeling, and inference, which is of immense importance due to increasingly diverse and nonexperimental data across a wide range of fields. The knowledge and skills readers gain from this book are also transferable to other areas, such as public health, business analytics, environmental studies, or spatio-temporal data visualization and analysis in general.
Genre: Non-Fiction > Tech & Devices
Download Instructions:
https://drop.download/xde4362v1rgw
https://turbobit.net/f1iftz3mpvzz.html
https://rg.to/file/cdb6f0941425361087a4abbbcdfa7a51
Trouble downloading? Read This.