sagemaker-python-sdk and sagemaker-training-toolkit
The Python SDK provides the high-level interface for orchestrating SageMaker training jobs, while the training toolkit is the low-level containerized runtime that executes those jobs, making them complements that work together in a producer-consumer relationship.
About sagemaker-python-sdk
aws/sagemaker-python-sdk
A library for training and deploying machine learning models on Amazon SageMaker
This is a Python library that helps machine learning engineers and data scientists train and deploy models on Amazon SageMaker. It simplifies the process of getting your data (from S3) into a training environment and then taking the trained model to make predictions. You can use popular frameworks like PyTorch or MXNet, or bring your own custom algorithms.
About sagemaker-training-toolkit
aws/sagemaker-training-toolkit
Train machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.
This project helps machine learning engineers or data scientists train their custom machine learning models within isolated Docker containers using Amazon SageMaker. You provide your training script and dependencies inside a Docker image, and the toolkit handles the environment setup, allowing SageMaker to run your training code efficiently. The output is a trained model ready for deployment.
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