Machine Learning is an experimental process by nature and involves a multitude of parameters, algorithms, and datasets each yielding different trained models that need to be evaluated against predefined objectives. For each permutation of these variables, data scientists need an easy way to keep track the work they’ve done and its results. SageMaker Experiments is a fully managed experiment management feature that gives data scientists the ability to track the parameters, metrics, datasets and any other artifacts related to their model training. With SageMaker Experiments, there is a single place to visualize your ML work, share experiments with colleagues, and deploy models straight from an experiment.
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