This project uses historical country-level CO2 emissions and socioeconomic indicators from 2000 to 2020 to create a model that predicts total CO2 emissions excluding LUCF in East Africa.
# linear Regression Model to Predict CO2 Emissions in East Africa
## Description of Mission and Problem
- My mission focuses on Climate Change and how to use technologies to address environmental challenges in Africa.
- The problem addressed here is the prediction of CO2 emissions trends to support improved climate-mitigation planning.
- The goal is to contribute practical, data-driven tools that support Africa's efforts in effective climate adaptation.
## Dataset Information
This project uses historical country-level CO2 emissions and socioeconomic indicators from 2000 to 2020 to create a model that predicts total CO2 emissions excluding LUCF in East Africa.
**Dataset:** `africa-co2-emissions.csv`
### Dataset Characteristics:
- **Rows:** 1,134
- **Columns:** 20 total (3 non-numeric, 17 numeric)
- **Source:** African countries CO2 emissions data
## Project Structure
```text
├── summative/
│ ├── API/
│ │ ├── app.py
│ │ ├── prediction.py
│ │ ├── requirements.txt
│ ├── FlutterApp/
│ │ ├── east_africa_co2_prediction_mobile_app
│ └── linear_regression/
│ ├── multivariate.ipynb
│ ├── data/
│ │ └── africa-co2-emissions.csv
│ └── final_model/
│ ├── best_linear_regression_model.joblib
│ └── fastapi_model_artifacts.joblib
└── README.md
```
## Setup Instructions
1. Clone or Download the Repository
```bash
git clone
github.com
cd linear_regression_model
```
2. Create and activate a Python virtual environment.
3. Install notebook dependencies:
- `pip install numpy pandas scikit-learn matplotlib joblib jupyter`
## How to Use the Notebook
### Method 1: Using Jupyter Notebook (Local)
```bash
# Navigate to project directory
cd linear_regression_model
# Launch Jupyter Notebook
jupyter notebook
# Open the file: multivariate.ipynb
```
### Method 2: Using Google Colab
1. Click the "Open in Colab" badge at the top of the notebook
2. Upload `africa-co2-emissions.csv` t …