These examples focus on the Amazon SageMaker Python SDK which allows you to write idiomatic TensorFlow or MXNet and then train or host in pre-built containers.
- CIFAR-10 with Chainer and ChainerMN
- Sentiment Analysis with Chainer
- MNIST with Chainer
- Sentiment Analysis with MXNet Gluon
- IRIS with Scikit-learn
- Visualize Amazon SageMaker Training Jobs with TensorBoard (CIFAR-10, TensorFlow 2.2)
- Managed Spot Training on TensorFlow
These examples focus on building standard Machine Learning models powered by frameworks like Apache Spark or Scikit-learn using SageMaker Python SDK.