hebel
A GPU-accelerated deep learning library for Python using CUDA via PyCUDA, implementing neural networks with various training methods.
What is hebel?
Hebel is a GPU-accelerated deep learning library for Python that implements neural network models using CUDA via PyCUDA. It provides feed-forward neural networks for classification and regression tasks along with various training methods like momentum, dropout, and early stopping. The library aims to make GPU-accelerated deep learning more accessible to Python developers.
Python developers and researchers who need GPU-accelerated neural network training for classification and regression tasks, particularly those working with CUDA-capable hardware.
Developers choose Hebel for its straightforward implementation of essential deep learning functionality with GPU acceleration, offering practical training methods and regularization techniques in a single Python package.
Overview
GPU-Accelerated Deep Learning Library in Python
Use Cases
Best For
- Training feed-forward neural networks with GPU acceleration
- Implementing classification models with regularization techniques
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