AmirFARES/ML-CO2-Prediction-UmojaHack-23

UmojaHack Africa 2023: Carbon Dioxide Prediction Challenge (BEGINNER) Participating in the UmojaHack Africa 2023 beginner-level competition. For more information about the challenge, visit zindi.africa . Check the README for more details. # UmojaHack Africa 2023: Carbon Dioxide Prediction Challenge (BEGINNER) 🌍📊 ## Introduction 🌟 Welcome to my Data Science and Machine Learning portfolio! This project is a result of my participation in the **UmojaHack Africa 2023: Carbon Dioxide Prediction Challenge (BEGINNER)** on Zindi. The challenge aimed to harness the power of machine learning and deep learning to predict carbon emissions in Africa using open-source CO2 emissions data from Sentinel-5P satellite observations. The goal is to assist governments and researchers in monitoring carbon emissions across the continent, even in areas with limited on-the-ground monitoring capabilities. I am proud to share my journey and achievements in this competition, where I ranked in the top 50%. Here's a glimpse of what I accomplished: ## About the Challenge 🌍 The challenge focused on predicting carbon emissions in Africa, addressing a critical aspect of climate change mitigation. Accurate monitoring of carbon emissions is crucial for understanding their sources and patterns. ### Challenge Details 📝 - **Prizes**: I competed for a chance to win monetary prizes, with the top three participants receiving cash rewards. Additionally, there were country prizes for the highest-ranking participants from specific countries. - **Evaluation**: The competition's performance metric was Root Mean Squared Error (RMSE), used to assess the accuracy of predictions. - **Datasets**: I utilized publicly-available, open-source CO2 emissions data obtained from Sentinel-5P satellite observations. The dataset included various features related to pollutants such as Sulphur Dioxide, Carbon Monoxide, Nitrogen Dioxide, and more. - **Challenges**: I faced challenges in feature engineering, model selection, and data preprocessing to create a robust predictive model. ## Project Files 📂 Here are the key files related to this project: - **Train.csv** - This dataset was used for training and contained target information. - **Test.csv** - …