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Repository Structure

This repository is organized into two main sections:

Library Code (visage/)

Production-ready ML library implementation.

visage/
├── __init__.mojo          # Main package
├── linalg/                # Linear algebra primitives
│   ├── __init__.mojo
│   └── ops.mojo          # vector_add, dot_product, matrix ops
├── nn/                    # Neural network modules (coming soon)
├── optim/                 # Optimizers (coming soon)
└── utils/                 # Utilities (coming soon)

Usage:

# Run tests
pixi run test

# Run examples
pixi run example-basic
pixi run example-nn

Learning Content (learn/)

Educational materials and step-by-step ML implementations.

learn/
├── README.md              # Full learning curriculum
├── src/                   # Block 0-11 learning projects
├── tests/                 # Learning exercise tests
├── scripts/               # Visualization scripts
├── results/               # Learning outputs
└── docs/                  # Learning guides, cheatsheets

Usage:

# Run learning projects
pixi run learn-vector-add
pixi run learn-dot-product

# Run learning tests
pixi run learn-test-all

# View visualizations
pixi run learn-viz-dot-product

Examples & Tests

  • examples/ - Library usage examples
  • tests/ - Library test suite
  • docs/ - Library API documentation

Quick Commands

# Library
pixi run test              # Run library tests
pixi run example-basic     # Basic operations demo
pixi run example-nn        # Neural network layer demo

# Learning
pixi run learn-vector-add  # Educational implementation
pixi run learn-test-all    # Learning exercise tests