Global Warming Analysis and Prediction Using Data Science
M. Purushotham Reddy, A. Aneesh, K. Praneetha, S. Vijay
Abstract
This paper analyzes the presentation of the machine learning algorithm, linear regression for prediction of global temperature and carbon emissions from previous years collected data over India. The forecast of long-term global warming and weather conditions could be of huge significance in various fields, such as climate research, farming, electricity, medicine, and many more. The data is calculated and predicted by linear regression since, of all the techniques that can be used, it obtains the highest precision for global warming and temperature. First ever step is to design a consistent, effective, reliable statistical data model on a broad data set and ultimately bring the relationship between average annual temperature and contributing factors to global warming. Global temperature reduction will benefit the entire globe because not only Humans but also various animals suffer from global warming.