# linear_algebra_ws
**Author:** [Willy Sajbeni](https://www.sajbeni.com)
**Email:** [willy@sajbeni.com](mailto:willy@sajbeni.com)
**GitHub:** [https://github.com/willySajbeni](https://github.com/willySajbeni)
**LinkedIn:** [https://www.linkedin.com/in/willysajbeni/](https://www.linkedin.com/in/willysajbeni/)
A minimal, transparent, and Open Source linear algebra library written in Rust.
## Why?
Most machine learning libraries today (TensorFlow, PyTorch, etc.) involve heavy tracking, telemetry, or hidden behaviors.
**LinearAlgebra-RS** is designed to be completely open, simple, educational, and 100% under your control — **no tracking, no spyware**.
This project starts from pure **linear algebra operations** and will evolve into a full **numerical computation engine**.
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## Current Features
✅ **Vector operations**
- Sum
- Subtraction
- Multiplication (element-wise)
- Division (element-wise)
✅ **User input for vectors and matrices**
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## Upcoming Features (Roadmap)
- **Matrix operations**
- Sum of Matrices
- Subtraction of Matrices
- Multiplication of Matrices
- Matrix Inversion
- Matrix Division (via Multiplication by Inverse)
- LU Decomposition
- Eigenvalues and Eigenvectors
- **Advanced Numerical Methods**
- Iterative Methods for Linear Systems (Jacobi, Gauss-Seidel)
- Direct Methods (Gaussian Elimination, LU Factorization)
- Conjugate Gradient Method (for sparse systems)
- **Gradient Optimizers**
- Simple Gradient Descent
- Stochastic Gradient Descent (SGD)
- Adam Optimizer
- RMSProp
- **Dimensionality Reduction**
- PCA (Principal Component Analysis)
- SVD (Singular Value Decomposition)
- LLE (Locally Linear Embedding)
- t-SNE (t-Distributed Stochastic Neighbor Embedding)
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## How to Run
Make sure you have **Rust** installed.
Clone this repository:
```bash
git clone https://github.com/willySajbeni/linear_algebra_ws.git
cd linear_algebra_ws
cargo run