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- W3215156572 abstract "Broadly ML is a subset of computer science which involves applying statistics over observed data to generate some process that can achieve some task. Python offers concise and readable code. While complex algorithms and versatile workflows stand behind ML and AI, Python’s simplicity allows the developer to write reliable systems. Developers get to put all their effort into solving an ML problem instead of focussing on the technical nuances of the language. Several prediction methods are popularly used to solve the problems. This study demonstrates how the ML model forecasts the number of upcoming COVID-19. Three kinds of predictions can be made by each of models—deaths, newly affected, and recoveries. The result Exponential Smoothing (ES) is performed by Linear Regression model (LR) and Least Absolute Shrinkage and Selection Operator (LASSO), and Support Vector Machine (SVM) performs poorly in all predictions." @default.
- W3215156572 created "2021-12-06" @default.
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- W3215156572 date "2021-11-28" @default.
- W3215156572 modified "2023-09-25" @default.
- W3215156572 title "A Survey on COVID-19 Case Analysis Using Machine Learning" @default.
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- W3215156572 doi "https://doi.org/10.1007/978-981-16-7305-4_24" @default.
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