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dc.contributor.advisorMai, Hoàng Bảo Ân
dc.contributor.authorTrần, Quang Tùng
dc.date.accessioned2025-02-21T07:45:18Z
dc.date.available2025-02-21T07:45:18Z
dc.date.issued2024
dc.identifier.urihttp://keep.hcmiu.edu.vn:8080/handle/123456789/6756
dc.description.abstractIn terms of both direct and indirect human casualties as well as the sociometric effects of the virus' spread, COVID-19 is one of the most viral viruses to have ever caused a pandemic. We have come to the conclusion that people's perceptions of how terrible a situation is are too subjective after understanding the risk in the rapid spread and harm of current epidemics and prior pandemics from the past. Although the damage caused by Covid has recently subsided because of vaccines and treatment drugs, it still exists and spreads silently with many new variants. Therefore, a web app can create statistics to assess and forecast epidemic trends in the context of covid's attempts to reemerge in China and the possibility of future pandemics at any time. In the worst-case scenario, I hope it can benefit the medical system and even help save more lives. In addition, I also built an MLOps process to automate and optimize the amount of data that is always updated and changes every day.en_US
dc.subjectBuildingen_US
dc.subjectWeb Appen_US
dc.subjectCovid-19 Reportingen_US
dc.subjectMlopsen_US
dc.subjectAzure Clouden_US
dc.titleBuilding Web App Of Covid-19 Reporting And Base On Mlops Approach In Azure Clouden_US
dc.typeThesisen_US


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