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Titlebook: Quality of Work-Life During Pandemic; Data Analysis and Ma Gitanjali Rahul Shinde,Soumi Majumder,Parikshit N. Book 2022 The Editor(s) (if a

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發(fā)表于 2025-3-21 17:10:55 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Quality of Work-Life During Pandemic
副標(biāo)題Data Analysis and Ma
編輯Gitanjali Rahul Shinde,Soumi Majumder,Parikshit N.
視頻videohttp://file.papertrans.cn/781/780397/780397.mp4
概述Presents impact of the COVID-19 pandemic on different sectors.Includes data analysis and mathematical modeling for each case study.Serves as a reference for researchers and practitioners in academia a
叢書名稱Studies in Big Data
圖書封面Titlebook: Quality of Work-Life During Pandemic; Data Analysis and Ma Gitanjali Rahul Shinde,Soumi Majumder,Parikshit N. Book 2022 The Editor(s) (if a
描述This book is focused on the impact of the COVID-19 pandemic on different sectors, i.e., education, real estate, health, and agriculture. The lockdown has been announced to control the spread of COVID-19 infections, however people/industries/organizations were not ready for lockdown and it has greatly affected their growth. The front workers in the healthcare sector suffered a lot as major responsibilities they needed to carry on. The education sector is also hampered due to the pandemic as schools, colleges were closed and teaching, examinations were carried out on online platforms. These platforms were new to teachers as well as students. The real estate sector faced tremendous loss in this pandemic as people were scared and no one ready to invest their money in such an uncertain time. The agriculture filed is also suffered as raw materials required for agriculture were not available readily due to pandemic...This book presents a survey that is conducted to understand the impact of COVID-19 on the quality of work-life in various sectors. The survey is focused majorly on four sectors, i.e. education, healthcare, real estate and agriculture. Data analysis is done based on responses
出版日期Book 2022
關(guān)鍵詞COVID-19; Quality of Work Life; Mathematical Modelling; Machine Learning; Principal Component Analysis; D
版次1
doihttps://doi.org/10.1007/978-981-16-7523-2
isbn_softcover978-981-16-7525-6
isbn_ebook978-981-16-7523-2Series ISSN 2197-6503 Series E-ISSN 2197-6511
issn_series 2197-6503
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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https://doi.org/10.1007/978-981-16-7523-2COVID-19; Quality of Work Life; Mathematical Modelling; Machine Learning; Principal Component Analysis; D
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Exploratory Data Analysis,ying any machine learning model to any datasets, it is necessary to understand the problem, deal with the missing values and noise, visualize the dataset, and to select the machine learning model to analyze the data. Following is an attempt to highlight the techniques of data analysis.
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