The spread of COVID-19 simulation is created using MESA library in this project. As a reference, SIR mathematical model for virus spread is used, which is type of compartmental model to represent the growth of agents ( Here, Positive/Negative/Suspected People) based on the differential equations.
In this project, I have scrapped news from google news using selenium and store the headlines as well as content of the news in a corpus folder. Then, I have done sentiment analysis on it used stopwords for learning purpose.
Cataract is the most widespread causes of blindness. Early detection or precautions could reduce the suffering from cataract to the patients and mitigate the visual disability from turning into total blindness. But the cost may cause difficulties to everybody’s early interventions, because the expertise trained eye specialists cannot be afforded by everyone. Based on the data provided on Kaggle.com, we are trying to build a model that predict whether the patient is suffering from cataract or not.
Developed a website for the audience of the University of Windsor, using Flask framework and Firebase as as data storage. User can submit their emotion at specific time and as specific location. Moreover, they can visualise the emotions on the map.