Zoe

Zoe is a comprehensive AI-powered financial assistant designed to enhance your financial decision-making processes. This application integrates several advanced AI features to provide users with robust tools for trading, market analysis, portfolio optimization, fraud detection, and personal financial management.

Features

1. AI-Powered Trading Bot:

   • Utilizes machine learning models to analyze market trends, historical data, and real-time news to make informed trading decisions.
   • Languages: Python (for machine learning models, data analysis), C++ or Java (for performance-critical components).
   • Libraries: TensorFlow, PyTorch, Scikit-learn.

2. Sentiment Analysis for Market Predictions:

   • Analyzes news articles, social media, and financial reports to gauge market sentiment and predict stock movements.
   • Languages: Python.
   • Libraries: NLTK, SpaCy, VADER, Hugging Face Transformers.

3. Portfolio Optimization Tool:

   • Helps investors optimize their portfolios by analyzing risk tolerance, financial goals, and market conditions.
   • Languages: Python (for optimization algorithms), R (for statistical analysis).
   • Libraries: NumPy, Pandas, SciPy, CVXPY.

4. Fraud Detection System:

   • Detects unusual transaction patterns and flags potential fraudulent activities in real-time.
   • Languages: Python.
   • Libraries: Scikit-learn, TensorFlow, PyTorch.

5. Personal Finance Advisor:

   • Provides personalized financial advice, budgeting tips, and investment recommendations based on user profiles and financial goals.
   • Languages: Python (for the backend AI models), JavaScript (for the frontend), HTML/CSS.
   • Libraries: Flask or Django (backend), React or Angular (frontend).

Installation

1. Clone the repository:

   git clone https://github.com/jurchiks33/zoe.git
   cd zoe

2. Set up a virtual environment:

   python3 -m venv env
   source env/bin/activate  # On Windows, use `env\Scripts\activate`

3. Install the required dependencies:

   pip install -r requirements.txt

Usage

1. Run the application:

   python app.py

2. Access the application in your web browser at http://localhost:5000.

Contributing

We welcome contributions to Zoe! Please follow these steps to contribute:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes and commit them (git commit -m 'Add some feature').
4. Push to the branch (git push origin feature-branch).
5. Open a pull request.

License

This project is licensed under the MIT License - see the ...... file for details.

Acknowledgements

• TensorFlow
• PyTorch
• Scikit-learn
• NLTK
• SpaCy
• Hugging Face

Contact

For any inquiries or feedback, please contact [......].