Rodgerdev/east-africa-fertilizer-project

As a team of data scientists, we built a machine learning system to predict crop production and forecast fertilizer consumption in East Africa. We applied models like Random Forest regressor and N-BEATS to support data-driven agricultural planning. The model was then deployed using streamlit. # East Africa Fertilizer Project This project focuses on analyzing fertilizer efficiency and its impact on agricultural productivity in East Africa. It encompasses data analysis, forecasting models, and visualizations to aid in understanding and improving fertilizer use in the region.​ ## Project Overview The East Africa Fertilizer Project aims to:​ Assess the efficiency of fertilizer usage in East African agriculture. Forecast agricultural productivity based on fertilizer application. Provide insights through data analysis and visualizations to support decision-making.​ ## Repository Contents east_africa_proj.ipynb: Jupyter Notebook containing data analysis and modeling. data/: Directory housing datasets used in the project. FORECASTING FERTILIZER EFFICIENCY AND AGRICULTURAL PRODUCTIVITY DATA REPORT.pdf: Comprehensive report detailing findings and methodologies. East_Africa_Fertilizer_Presentation.pptx: Presentation summarizing key insights and results. .gitignore: Specifies files and directories to be ignored by Git.​ GitHub ## Getting Started Prerequisites Ensure you have the following installed:​ Python 3.x Jupyter Notebook Required Python libraries (e.g., pandas, numpy, matplotlib, scikit-learn)​ ## Contributing Contributions are welcome! If you have suggestions or improvements, please fork the repository and submit a pull request.​ ## License This project is licensed under the MIT License. See the LICENSE file for details.​ ## Acknowledgments Special thanks to all model kombat members who made this project possible.