
Frameworks
飞桨PaddlePaddle
PaddlePaddle provides a deep learning platform, supporting dynamic and static graphs, carefully selected algorithm models, originating from industrial practice, offering seamless integration from training to inference.
【Application Scenarios】
- Work scenarios: Research and application of deep learning technologies
- Life scenarios: AI learning and development
【Target Users】
- Deep learning developers
- AI researchers
- Enterprise developers
【Core Features】
- Unified dynamic and static graphs, balancing flexibility and efficiency
- Carefully selected algorithm models with the best application effects and official support
- Truly originating from industrial practice, providing the industry's strongest large-scale parallel deep learning capability
- Integrated inference engine design, offering seamless integration from training to multi-end inference
- The only platform providing systematic technical services and support for deep learning
【Is it free】
- Yes
【Community Ecosystem】
- Rich tutorials and competitions
- Developer community discussions and technical sharing
- GitHub official repository
【Summary】
- PaddlePaddle is an open-source deep learning platform based on industrial practice, dedicated to making the innovation and application of deep learning technologies simpler.
- It provides seamless integration from training to multi-end inference, supports multiple hardware and operating systems, and has powerful large-scale parallel deep learning capabilities.
Content assisted by AI. Please review carefully.
Provide documentation and tutorials for the JAX library, used for high-performance numerical computation and machine learning research.