AWS Posted September 1, 2022 Share Posted September 1, 2022 SageMaker Autopilot automatically builds, trains and tunes the best machine learning models based on your data, while allowing you to maintain full control and visibility. Starting today, when creating Autopilot experiment to train a machine learning model, you can customize the splits of data used for training and validation of models. By default Autopilot splits the specified dataset into 80-20 percent splits reserved for training and validation respectively. With this release, you can customize the training and validation data split percentages or alternatively provide two datasets, one for training and another for validation. This feature is available for use in both Amazon SageMaker Studio and SageMaker Autopilot API. View the full article Quote Link to comment Share on other sites More sharing options...
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