maeshakib/CO-Prediction-Machine-Learning-Model-

Machine Learning model to predict CO₂ emissions in Rwanda using Sentinel-5P satellite data # CO-Prediction-Machine-Learning-Model- Machine Learning model to predict CO₂ emissions in Rwanda using Sentinel-5P satellite data Bangladesh Demographics Dashboard, purpose of the analysis is to explore and visualize urban data from Bangladeshi cities, uncovering patterns in population, infrastructure, and socio-economic factors. Using the Bangladesh Food Prices Dataset dataset from Kaggle, the Tableau dashboard aims to provide actionable insights for urban planning and policy-making. Data set Link. Tableau Bangladesh Population Dashboard Link. Report Link 1.1 Background and Context Monitoring CO₂ is an important area of tackling climate change. Carbon dioxide(CO2 ) is a major GHG gas that makes up 80% of the GHG emissions. Therefore, the reduction of CO2 emissions will help in reducing GHG emissions produced by the county. Accurate forecasting of CO2 1.2 Problem Statement 1.3 Research Objectives The primary objective of this research is • To build a machine learning model that predicts CO₂ emissions in Rwanda with high accuracy using open-source CO2 emissions data from Sentinel-5P satellite observations. This study will employ a range of machine learning techniques, including linear and non-linear models, and compare their effectiveness in handling Rwanda's specific data characteristics. • The scope of the research will be confined to CO₂ emissions related to economic and population data, energy consumption, and transportation, aiming to understand which factors have the most significant impact on Rwanda's emission profile. The study will not account for external, unmeasurable factors such as climate policies that may indirectly influence emissions. • Comparing the performance of all models to find the best forecasting model. • Forecasting the future CO2 emissions using the best model. • Publishing the information so that appropriate policies can be implemented. 1.4 Research Questions The following key research question will be explored: Which machine …