yahiasaidi-art/algeria-ml-forecasting

Machine Learning for Economic Forecasting in Algeria # algeria-ml-forecasting Machine Learning for Economic Forecasting in Algeria # Machine Learning for Economic Forecasting in Algeria This repository supports the research paper: **"Machine Learning-Based Economic Forecasting in Resource-Constrained Economies: A Case Study of Algeria"** ## 📄 Overview This study evaluates five machine learning models — Linear Regression, ARIMA, Random Forest, Prophet, and LSTM — for forecasting key macroeconomic indicators in Algeria: - GDP Growth - Inflation - Unemployment Models are trained on 2003–2019 data and evaluated on out-of-sample forecasts (2020–2023), demonstrating that ML reduces forecasting errors by 25–40% compared to traditional methods. ## 📂 Files - `algeria_forecasting.ipynb`: Full Jupyter notebook with code, models, and evaluation - `data.csv`: Cleaned dataset (2003–2023) used in the analysis ## 🚀 How to Use 1. Download the notebook and open in: - Google Colab (recommended) - Jupyter Notebook - VS Code 2. Install required libraries: ```bash pip install pandas numpy scikit-learn prophet tensorflow matplotlib seaborn statsmodels