elshaday-0412/Amharic-Sentiment-Analysis

# Amharic Sentiment Analysis An Artificial Intelligence and Natural Language Processing (NLP) project for classifying Amharic text into sentiment categories using Machine Learning. --- ## 📖 Overview Amharic is one of the least represented languages in Natural Language Processing research. This project aims to develop a sentiment analysis system capable of predicting whether an Amharic sentence expresses a **positive**, **negative**, or **neutral** opinion. The project demonstrates the complete machine learning pipeline, from data preprocessing to model deployment through a web interface. --- ## ✨ Features - Amharic text preprocessing - Text cleaning and normalization - Machine Learning sentiment classification - Trained model saving and loading - Web interface for sentiment prediction - Simple and user-friendly design --- ## 🏗️ Project Structure ``` . ├── app.py ├── data/ ├── frontend/ ├── model/ ├── saved_models/ ├── static/ ├── utils/ ├── requirements.txt └── README.md ``` --- ## 🛠 Technologies Used - Python - Flask - Scikit-learn - Pandas - NumPy - Joblib - HTML - CSS - JavaScript --- ## ⚙️ Installation Clone the repository ```bash git clone github.com ``` Navigate into the project ```bash cd your-repository ``` Install dependencies ```bash pip install -r requirements.txt ``` Run the application ```bash python app.py ``` --- ## 📊 Machine Learning Workflow 1. Data Collection 2. Data Cleaning 3. Text Preprocessing 4. Feature Extraction 5. Model Training 6. Model Evaluation 7. Prediction 8. Deployment --- ## 🎯 Applications - Social media opinion analysis - Customer feedback analysis - Product review classification - Public opinion monitoring - Research on Ethiopian languages --- ## 📸 Screenshots You can include screenshots here, for example: - Home Page - Prediction Result - Model Accuracy - User Interface --- ## 🚀 Future Improvements - Deep Learning models (LSTM, GRU, Transformers) - BERT …