You can learn TensorLayerX quickly from the following two examples:
Multi-layer perceptron (MNIST), simple usage and supports multiple backends. Classification task, see mnist_mlp.py.
Convolutional Network (CIFAR-10), simple usage and supports multiple backends. Classification task, see cifar10_cnn.py.
More official tutorials can be found in the resources below:
[Examples](https://github.com/tensorlayer/TensorLayerX/tree/main/examples) for tutorials
[GammaGL](https://github.com/BUPT-GAMMA/GammaGL) is series of graph learning algorithm
[TLXZoo](https://github.com/tensorlayer/TLXZoo) a series of pretrained backbones
[TLXCV](https://github.com/tensorlayer/TLXCV) a series of Computer Vision applications
[TLXNLP](https://github.com/tensorlayer/TLXNLP) a series of Natural Language Processing applications
[TLX2ONNX](https://github.com/tensorlayer/TLX2ONNX/) ONNX model exporter for TensorLayerX.
[Paddle2TLX](https://github.com/tensorlayer/paddle2tlx) model code converter from PaddlePaddle to TensorLayerX.