sagemaker training toolkit

We have hosted the application sagemaker training toolkit in order to run this application in our online workstations with Wine or directly.

Quick description about sagemaker training toolkit:

Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. The SageMaker Training Toolkit can be easily added to any Docker container, making it compatible with SageMaker for training models. If you use a prebuilt SageMaker Docker image for training, this library may already be included. Write a training script (eg. train.py). Define a container with a Dockerfile that includes the training script and any dependencies.

Features:

• Pass arguments to the entry point using hyperparameters
• To train a model using the image on SageMaker, push the image to ECR and start a SageMaker training job with the image URI
• Read additional information using environment variables
• Get information about the container environment
• Execute the entry point
• Create a Docker image and train a model

Programming Language: Python.
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