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Please check following link for using SDK method for best training jobs: https://sagemaker.readthedocs.io/en/stable/api/training/tuner.html
Also, please refer to following blog for using model attributes to track training: https://aws.amazon.com/blogs/machine-learning/amazon-sagemaker-now-comes-with-new-capabilities-for-accelerating-machine-learning-experimentation/
Basically SageMaker persists hyperparameters and model S3 ARN for training job in its metadata store. Data is not versioned but only S3 ARNs
Some links for reference:
https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-how-it-works.html
https://docs.aws.amazon.com/sagemaker/latest/dg/xgboost-tuning.html
Hi,
You may want to explore SageMaker Automatic Model Tuning (AMT): https://aws.amazon.com/sagemaker/automatic-model-tuning/
See this blog for implementation: https://aws.amazon.com/blogs/machine-learning/optimize-hyperparameters-with-amazon-sagemaker-automatic-model-tuning/
Best,
Didier
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