Brewing up custom ML models on AWS SageMaker

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Brewing up custom ML models on AWS SageMaker



Iam new with SageMaker and I try to use my own sickit-learn algorithm . For this I use Docker.
I try to do the same task as described here in this github account : https://github.com/awslabs/amazon-sagemaker-examples/blob/master/advanced_functionality/scikit_bring_your_own/scikit_bring_your_own.ipynb



My question is should I create manually the repository /opt/ml (I work with windows OS) ?


/opt/ml



Can you explain me please?



thank you




1 Answer
1



You don't need to create /opt/ml, SageMaker will do it for you when it launches your training job.


/opt/ml



The contents of the /opt/ml directory are determined by the parameters you pass to the CreateTrainingJob API call. The scikit example notebook you linked to describes this (look at the Running your container sections). You can find more info about this in the Create a Training Job section of the main SageMaker documentation.


/opt/ml






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