Amazon SageMaker Now Supports TensorFlow 2.0

[Amazon SageMaker](/sagemaker/) now supports Tensorflow 2.0 as a pre-built deep learning container. This latest version provides significant updates to the existing API, simplifies eager execution, offers a new dataset manager, and more. You can now use this container on SageMaker, and take advantage of many advanced capabilities, such as building models using the SageMaker SDK in managed notebooks, hyperparameter tuning, and distributed training. You can also bring your own container for custom models by building off our base [containers](https://github.com/aws/sagemaker-tensorflow-container). Click [here](https://docs.aws.amazon.com/sagemaker/latest/dg/tf.html) for more information on using TensorFlow with SageMaker, and [here](https://github.com/awslabs/amazon-sagemaker-examples/tree/master/sagemaker-python-sdk/tensorflow%5Fscript%5Fmode%5Ftraining%5Fand%5Fserving) to see an example notebook of starting a job with Tensorflow 2.0\.