Guides

PaddlePaddle (PArallel Distributed Deep LEarning) is a simple, efficient and extensible deep learning framework.

Please refer to PaddlePaddle Github for details, and Release Note for features incorporated in current version.

Let’s start with studying basic concept of PaddlePaddle:

• Model Development

• More Uses for Model Development

• Dygraph to Static Graph : Introduce the transformation of dygraph to static graph.

• Inference and Deployment : Introduce the method of using the trained model to inference.

• Distributed Training : Introduce how the PaddlePaddle uses distributed training

• Performance Improving : Introduce how to improve performance of PaddlePaddle.

• Model Convert : Introduce how to convert your model to PaddlePaddle.

• FLAGS : Introduce the envirenment flags in paddle.