Starting today, AWS Clean Rooms now supports training custom ML models on data in Parquet file format. Parquet is a free and open-source column-oriented data storage format that provides efficient data compression and encoding schemes with enhanced performance.
With AWS Clean Rooms ML custom modeling, you and your partners can train a custom ML model using collective datasets at scale without having to share sensitive intellectual property. By creating ML input channels in Parquet file format, you can process large volumes of data more efficiently and encode non-text based data allowing you to train on images, and other binary encoded datatypes.
AWS Clean Rooms ML helps you and your partners apply privacy-enhancing controls to safeguard your proprietary data and ML models while generating predictive insights—all without sharing or copying one another’s raw data or models. For more information about the AWS Regions where AWS Clean Rooms ML is available, see the AWS Regions table. To learn more, visit AWS Clean Rooms ML.
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Source: Amazon Web Services
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