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Tag: amazon-sagemaker

entry_point file using XGBoost as a framework in sagemaker

Looking at the following source code taken from here (SDK v2): I wonder where the file has to be placed please? So far I used XGBoost as a built-in algorithm from my local machine with similar code (i.e. I span up a training job remotely). Thanks! PS: Looking at this, and source_dir, I wonder if one can upload Python

Isolation Forest vs Robust Random Cut Forest in outlier detection

I am examining different methods in outlier detection. I came across sklearn’s implementation of Isolation Forest and Amazon sagemaker’s implementation of RRCF (Robust Random Cut Forest). Both are ensemble methods based on decision trees, aiming to isolate every single point. The more isolation steps there are, the more likely the point is to be an inlier, and the opposite is

Why package is not updated even the lifecycle script has been executed successfully in SageMaker?

I wanted to update pandas version in ‘conda-python3’ in SageMaker, I’ve followed the steps in this page, and linked the new configuration to my instance, CloudWatch log shows me the script has been executed successfully, but when I restart my instance and print out the panda version, it’s still showing the old version 0.24.2, I don’t understand why? This is