🧠 Neuronix Vector Engine (NVE v9.9.9)

Lead Architect: Nosrat Jahan

Neuronix is a high-performance Machine Learning engine designed for profile-based recommendation synthesis. It leverages vectorized linear algebra to map user preferences into a multi-dimensional latent space for precision matching.

🚀 Technical Highlights

• Algorithm: Latent-Space Collaborative Filtering (UBCF).
• Computation Core: NumPy-optimized Vectorization.
• Alignment Metric: High-fidelity Cosine Similarity.
• Interface: Enterprise-grade CLI with real-time telemetry.

📊 Mathematical Logic

The engine utilizes the Cosine Alignment formula to calculate the spatial orientation between user vectors:

$$similarity = \cos(\theta) = \frac{\mathbf{A} \cdot \mathbf{B}}{|\mathbf{A}| |\mathbf{B}|}$$

This ensures the identification of the Nearest Neighbor profile with maximum mathematical accuracy.

⚙️ Installation & Usage

1. Clone the repository:

   git clone [https://github.com/Nosrat-Jahan/Neuronix-Vector-Engine.git](https://github.com/Nosrat-Jahan/Neuronix-Vector-Engine.git)