Elevado, Jane Irish B., <br/><br/>
Data analysis of Nabua covid-19 cases using machine learning algorithm /  
Jane Irish B. Elevado, [and 4 others]. 
 - 139 leaves. 
<br/><br/>Undergraduate Theses (BSCS) - Computer Science 
<br/><br/>Includes bibliographical references. 
<br/><br/> The practice of storing, organizing, and analyzing data for commercial objectives is known as data analytics. Key decision-makers are informed through this process, which enables them to base crucial strategic judgments on facts rather than intuition. Previous data are examined in order to forecast trends, enhance outreach and even better control the spread of illnesses. That is what this paper addresses using machine learning strategies such as linear regression to study and tried to predict possible future outcomes and probabilities, for instance, the growth of covid cases for the future years or the connection of certain factors in the spread and behavior of the said virus. With the use of this regression strategies, covid 19 and other key factors relations are analyzed. All the three created models yielded a favorable result with the logistic regression having the lessed amount of errors (0.0) for almost all the metrics used. The model shows that for this year there will be less than 40 cases and for the year 2023 and 2024 the cases is below the 20 mark meaning that for the next two years there will be less than 20 covid Cases on Nabua.