rustorch 0.6.29

Production-ready PyTorch-compatible deep learning library in Rust with special mathematical functions (gamma, Bessel, error functions), statistical distributions, Fourier transforms (FFT/RFFT), matrix decomposition (SVD/QR/LU/eigenvalue), automatic differentiation, neural networks, computer vision transforms, complete GPU acceleration (CUDA/Metal/OpenCL), SIMD optimizations, parallel processing, WebAssembly browser support, comprehensive distributed learning support, and performance validation
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# RusTorch Quick Start Guide

This file provides quick access to getting started with RusTorch. For detailed documentation, see the main [README.md](README.md).

## 🚀 Quick Installation

```bash
# Run the appropriate quick start script
./scripts/quick_start.sh              # Basic setup
./scripts/quick_start_rust_kernel.sh  # With Rust Jupyter kernel
./scripts/quick_start_webgpu.sh       # With WebGPU support
```

## 📚 Documentation Links

- **Main Documentation**: [README.md](README.md)
- **Jupyter Setup**: [README_JUPYTER.md](README_JUPYTER.md)
- **CoreML + Jupyter**: [README_COREML_JUPYTER.md](README_COREML_JUPYTER.md)
- **Changelog**: [CHANGELOG.md](CHANGELOG.md)

## 📁 Directory Structure

- `scripts/` - Installation and setup scripts
- `config/` - Configuration files (Docker, environment, etc.)
- `docker/` - Docker container definitions
- `tools/` - Development and benchmarking tools
- `examples/` - Example code and demos
- `docs/` - Detailed documentation
- `tests/` - Test suites