AWS Machine Learning Blog

Tag: Data Version Control

Solution architecture and workflow

Track your ML experiments end to end with Data Version Control and Amazon SageMaker Experiments

Data scientists often work towards understanding the effects of various data preprocessing and feature engineering strategies in combination with different model architectures and hyperparameters. Doing so requires you to cover large parameter spaces iteratively, and it can be overwhelming to keep track of previously run configurations and results while keeping experiments reproducible. This post walks […]