Machine Learning / Linear Algebra lib writen in Rust 🦀

• Rust

For the version 1.0.0 this library should cover all features bellow:

• Matrix operations
• Vector operations
• Scalar operations
• Norms
• Eigenvalues and eigenvectors
• Linear system solutions
• Singular value decomposition
• Matrix factorization
• Convolutions
• Broadcasting

• Data processing
• Model selection and training
• Model evaluation and validation
• Hyperparameter tuning and optimization
• Deployment and integration(maybe not?)
• Documentation

All features are listed on issues/projects tab

• Feel free to pick one that's not assign or contribute with the assigned person
• Follow the Github flow to contribute to this project.
• Conventional commits for concise messages.

• Use 'rustdoc' to generate documentation
• Describe your code what it does and how it does it.
• Give examples

• Write tests
• Make sure that you cover all your code with tests and that the all precedent tests are not broken by your changes.

PR's without the contributing checklist above will not be accepted.