Can I use AWS Sagemaker without S3
Can I use AWS Sagemaker without S3 If I am not using the notebook on AWS but instead just the Sagemaker CLI and want to train a model, can I specify a local path to read from and write to? 2 Answers 2 If you use local mode with the SageMaker Python SDK, you can train using local data: from sagemaker.mxnet import MXNet mxnet_estimator = MXNet('train.py', train_instance_type='local', train_instance_count=1) mxnet_estimator.fit('file:///tmp/my_training_data') However, this only works if you are training a model locally, not on SageMaker. If you want to train on SageMaker, then yes, you do need to use S3. For more about local mode: https://github.com/aws/sagemaker-python-sdk#local-mode As far as I know, you cannot do that. Sagemaker's framework and estimator API makes it easy for SageMaker to feed in data to the model at every i...