🦀 Rust Neural Network Learning Project 🧠

📋 Project Overview

This project is designed to help me learn the basics of the Rust programming language 🦀 while exploring neural network concepts 🤖. The primary objective is to implement a simple neural network from scratch using Rust, enabling me to deepen my understanding of both Rust and fundamental machine learning principles.

🎯 Goals

• 🚀 Learn Rust: Understand Rust's ownership model, concurrency, and performance optimizations.
• 🔧 Build Neural Network Components: Implement core neural network elements (e.g., neurons, layers, activation functions).
• 🧩 Explore Training Algorithms: Experiment with backpropagation and other training methods.
• 💻 Create CLI Interface: Develop a command-line interface for interacting with and testing the network.

🛠️ Installation & Setup

1. Ensure you have Rust installed.
2. Clone the repository:

   git clone https://github.com/emy3/flowering.git

3. Navigate into the project directory:

   cd flowering

4. Build and run the project:

   cargo run

📚 Learning Resources

• The Rust Programming Language 📘
• Rust by Example 💡
• Neural Networks and Deep Learning Book 🧠

🚧 Project Roadmap

1. Implement basic neural network components (neurons, layers, forward propagation).
2. Add support for common activation functions (ReLU, Sigmoid, etc.).
3. Implement backpropagation and gradient descent.
4. Create example datasets and train the network.
5. Expand functionality for more complex networks.

🤝 Contributing

Feel free to open issues or submit pull requests if you'd like to contribute! 💪

📄 License

This project is licensed under the MIT License. See the LICENSE file for details.

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Happy coding! 🎉