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Starting today, you can invoke SageMaker Autopilot from SageMaker Data Wrangler to automatically train, tune and build machine learning models. SageMaker Data Wrangler reduces the time to aggregate and prepare data for machine learning (ML) from weeks to minutes. 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. Previously, customers used Data Wrangler to prepare their data for machine learning and Autopilot for training machine learning models independently. With this unified experience, you can now prepare your data in SageMaker Data Wrangler and easily export to SageMaker Autopilot for model training. With just a few clicks, you can automatically build, train, and tune machine learning models, making it easier to automatically employ state-of-the-art feature engineering techinques, train high quality machine learning models, and gain insights from your data faster. View the full article -
Today we are announcing the general availability of splitting data into train and test splits with Amazon SageMaker Data Wrangler. Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes. With SageMaker Data Wrangler, you can simplify the process of data preparation and feature engineering, and complete each step of the data preparation workflow, including data selection, cleansing, exploration, and visualization from a single visual interface. With SageMaker Data Wrangler’s data selection tool, you can quickly select data from multiple data sources, such as Amazon S3, Amazon Athena, Amazon Redshift, AWS Lake Formation, Snowflake, and Databricks Delta Lake. View the full article
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