Paper PublishingCOVID-19 Future Forecasting Using Supervised Machine Learning Models
Objective
The objective of this project is about novel coronavirus also known as COVID-19 predictions. The COVID-19 has proved a potential threat to human life. It causes tens of thousands of deaths and the death rate is increasing day by day throughout the globe. To contribute to this pandemic situation control, this study attempts to perform future forecasting on the death, recoveries and cases. Our model will help to create future predictions which reduce the burden to the people who are continuously working on covid predictions.
Abstract
Machine learning (ML) based forecasting mechanisms have proved their significance to anticipate in adjective outcomes to improve the decision making on the future course of actions. The ML models have long been used in many application domains which needed the identification and prioritization of adverse factors for a threat. Several prediction methods are being popularly used to handle forecasting problems. This study demonstrates the capability of ML models to forecast the number of upcoming patients affected by COVID-19 which is presently considered as a potential threat to mankind. Our proposed method integrates a numeral of approach, intended to advance the cooperativeness of the explore operation. In this work, we develop the application of covid-19 which can be able to predict outcomes from Total Confirmed cases, Fatalities and Recoveries.
KEYWORDS: Covid-19, Total Confirmed Cases, Fatalities, and Recoveries.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
SOFTWARE SPECIFICATIONS:
- Technology: Machine Learning, Application.
- Libraries: Pandas, Numpy, Sklearn.
- Version: Python 3.6+
- Server-side scripts: HTML, CSS, JS
- Frame works: Flask
- IDE: Pycharm
HARDWARE SPECIFICATIONS:
- RAM: 8GB, 64-bit os.
- Processor: I3/Intel processor
- Hard Disk Capacity: 128 GB +
Learning Outcomes
- About Python.
- About PyCharm.
- About Pandas.
- About Numpy.
- About HTML.
- About CSS.
- About Javascript.
- About Database.
- About Machine Learning.
- About Artificial Intelligent.
- About how to use the libraries.
- Cloud Overview.
- Terminology of cloud.
- Virtualization.
- About how to create the registration table in sql.
- About model choosing.
- About future outcomes for the covid-19
- About how to generate the predictions with python code.
- Project Development Skills:
- Problem analyzing skills.
- Problem solving skills.
- Creativity and imaginary skills.
- Programming skills.
- Deployment.
- Testing skills.
- Debugging skills.
- Project presentation skills.
- Thesis writing skills.
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Disclaimer - Takeoff Edu Group Projects, are not associated or affiliated with IEEE, in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, and not projects of or by IEEE.
