A machine learning-powered stock prediction platform that analyzes news sentiment to provide BUY/SELL recommendations with AI-powered explanations.

• 🤖 Machine Learning Model: Random Forest trained on historical news sentiment vs stock performance
• 📰 Real-time News Analysis: Alpha Vantage API integration for live news sentiment
• 🧠 AI Explanations: OpenAI GPT-3.5-turbo powered explanations for each recommendation
• 📊 Top 5 BUY Recommendations: Auto-generated list of highest confidence stocks
• 🎨 Professional UI: Clean, modern financial platform design
• ⚡ Live Predictions: Real-time analysis for any stock ticker

• Backend: Flask (Python)
• ML Model: Random Forest (scikit-learn)
• AI: OpenAI GPT-3.5-turbo
• Data: Alpha Vantage API
• Frontend: HTML/CSS/JavaScript
• Styling: Professional white/blue theme

git clone <your-repo-url>
cd sentiswing

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

pip install -r requirements.txt

Create a .env file in the root directory:

# OpenAI API Configuration
OPENAI_API_KEY=your_openai_api_key_here

# Flask Configuration
FLASK_ENV=development
FLASK_DEBUG=True

• OpenAI API Key: Get from https://platform.openai.com/api-keys
• Alpha Vantage API Key: Get from https://www.alphavantage.co/support/#api-key

source venv/bin/activate
python app.py

Visit http://localhost:5000 to use the application.

1. Search for any stock (e.g., AAPL, NFLX, TSLA)
2. View ML prediction with confidence score
3. Click "Get AI Explanation" for detailed analysis
4. Browse Top 5 BUY recommendations on the homepage

sentiswing/
├── app.py                      # Flask backend
├── sentiswing_trainer.py       # ML model training
├── sentiswing_predictor.py     # Prediction logic
├── templates/
│   └── index.html              # Frontend dashboard
├── .env                        # Environment variables (not in git)
├── .gitignore                  # Git ignore rules
├── requirements.txt            # Python dependencies
└── data files...

1. "Let me search NFLX..." → Shows BUY 98.9% confidence
2. "Here's why our AI recommends this..." → Click AI Explanation button
3. "The AI explains the reasoning based on sentiment analysis" → Shows professional explanation

Perfect for hacker track competitions with:

• Real ML model implementation
• Multiple API integrations
• Professional presentation
• Live demo capabilities

MIT License - feel free to use for hackathons and projects!