Aim:

            To detect the COVID-19 using Machine Learning Classification Algorithms

Abstract:

          The Corona-virus 2019(COVID-19), which first occurs in Wuhan city of China in December 2019, spread quickly around the world and became a plague. Due to the regular increase in cases, the number of COVID-19 test kits available in the hospital is minimal. Since an automated detection system is needed as an alternative diagnosis to prevent COVID-19 from spreading among people. It is necessary to detect the positive cases as early as possible so as to prevent the further spread of this disease. Application of Machine learning techniques coupled with the COVID-19 dataset. Our goal is to enhance the performance of the model by removing unnecessary and insignificant attributes from the dataset and only collecting those that are most informative and useful for the classification task. Thus the main focus of the system is to make use data analytics to predict the presence of the Virus or not.

Proposed System:

          The Covid-19 pandemic has consumed the world, with 192 countries affected and global cases nearing 150 million. To overcome the fallback in the existing system we propose a Machine learning based system to overcome the patient from the afraid and make it as user friendly. We have proposed an automatic prediction of Covid-19 using Covid dataset. The final result shows in Web app.