Neura is an open-source, zero-dependency machine learning library written in Go. The goal of Neura is to provide a fast, efficient, and minimalistic solution for machine learning tasks, tailored to the simplicity and performance focus of Go.
Neura is currently in its early stages. The core functionality is being developed, and contributions, feedback, and suggestions are highly encouraged.
Note:
This library is not ready for production (or any other, lol) use yet.
- Zero Dependencies: Neura is designed with no external dependencies, keeping the library lightweight and fast.
- Machine Learning Algorithms: Support for common machine learning algorithms, including:
- Linear Regression
- K-Means Clustering
- Decision Trees
- Performance-Focused: Built with Go’s performance strengths in mind, ensuring minimal overhead.
- Developer-Friendly API: A simple, intuitive interface designed for Go developers.
- Extensible Design: The library is structured to allow easy expansion with additional models and tools.
# Coming soon
// Example usage of Neura will be added here soon.
- Basic Linear Algebra Operations
- Data Preprocessing Utilities
- Regression Models (e.g., Linear, Logistic)
- Clustering Algorithms (e.g., K-Means, DBSCAN)
- Model Evaluation Metrics (e.g., Accuracy, Precision)
- Neural Networks (Future Plans)
All contributors are welcomed! Whether you're new to Go or a seasoned developer, feel free to fork the repository, make changes, and submit a pull request. Contribution guidelines will be provided soon.
This project is licensed under the MIT License - see the LICENSE file for details. (Honestly, I have no idea about this license - ChatGPT recommended me to use that one)
Feel free to text or mail me for any queries or help.
- Email: adilkhanislam9@icloud.com
- Telegram: islamchique