Predictive Analytics of COVID-19 for Subcontinent Countries

Project Title

Predictive Analytics of COVID-19 for Subcontinent Countries

Project Area of Specialization Artificial IntelligenceProject Summary

The outbreak of COVID-19 has created devastating situations throughout the world. The COVID-19 is rapidly increasing day by day. Data Science can be deployed very effectively to predict the growth of the epidemic and design strategies and policies to manage its spread. This project applies a Machine Learning model to analyze and predict the growth of the epidemic. An ML-based model has been applied to predict the potential threat of COVID-19 in sub-continent countries. A data-driven approach with higher accuracy as here can be very useful for a proactive response from the government and citizens.

Project Objectives

Our main objective of this project is to predict the growth of COVID-19 in sub-continent countries which include Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka. The first step is to get the COVID-19 dataset of these countries. The next step is to import data in a jupyter notebook by using python library pandas then cleaning data as irrelevant data will affect our prediction. Now we will be visualizing data by using python library Matplotlib to identify useful patterns and meaningful relationships. Now it’s time to build a machine learning model using different machine learning algorithms which includes Linear Regression, Logistic Regression, Polynomial Regression, K Nearest Neighbor, and Random Forest then we will be training our model on historical data and predict covid-19 cases for sub-continent countries and provide a predictive analytics report.

Project Implementation Method

The first step is to get the COVID-19 dataset of these countries. The next step is to import data in a jupyter notebook by using python library pandas then cleaning data as irrelevant data will affect our prediction. Now we will be visualizing data by using python library Matplotlib to identify useful patterns and meaningful relationships. Now it’s time to build a machine learning model using different machine learning algorithms which includes Linear Regression, Logistic Regression, Polynomial Regression, K Nearest Neighbor, and Random Forest then we will be training our model on historical data and predict covid-19 cases for sub-continent countries and provide a predictive analytics report.

Benefits of the Project

This project applies a Machine Learning model to analyze and predict the growth of the epidemic. An ML-based model has been applied to predict the potential threat of COVID-19 in sub-continent countries. A data-driven approach with higher accuracy as here can be very useful for a proactive response from the government and citizens.

Technical Details of Final Deliverable

Language: Python
IDE: Jupyter Notebook
Machine Learning Algorithms:

• Linear Regression 
• Logistic Regression 
• Polynomial Regression 
• K Nearest Neighbor
• Random Forest

Final Deliverable of the Project Software SystemCore Industry MedicalOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	33000
ASUS NVIDIA GeForce GTX 1050Ti 4GB Graphic Card	Equipment	1	33000	33000