Hebel
Hebel is a Python library designed for GPU-accelerated deep learning, utilizing CUDA through PyCUDA. It supports various neural network architectures, including feed-forward networks for classification and regression, while offering advanced training techniques such as momentum and dropout. Regularization options like L1 and L2 weight decay enhance model performance.
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Top Hebel Features
- GPU acceleration with CUDA
- Supports multiple neural network types
- Configurable activation functions
- Momentum and Nesterov momentum
- Dropout regularization
- L1 and L2 weight decay
- Stochastic gradient descent implementation
- Python-based library
- Easy installation via PyPi
- Cross-platform compatibility
- Example yaml configuration files
- Model and log management
- User feedback integration
- Documentation available online
- Future model plans
- GitHub issue tracking
- Research citation support
- Maintained by expert developer
- Active community engagement
- Lever analogy inspiration.
