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New AWS SageMaker Autopilot Automates Machine Learning Modeling

On Tuesday Amazon announced SageMaker Autopilot, a new tool for its SageMaker machine learning platform that the company says will automate machine learning tasks like data preprocessing, training parameters and classification, including correcting for training issues like overfitting.

SageMaker is the company's managed service for machine learning. Within SageMaker, companies can work within the SageMaker Studio IDE environment to "stitch together" various tools, including SageMaker Neo, a training tool; SageMaker Augmented AI, for "human review" of model predictions; SageMaker Model Tuning for automated optimization; and, now, SageMaker Autopilot, for automating the process of building and training machine learning models.

As for how it works, Amazon shared the following:

SageMaker Autopilot first inspects your data set, and runs a number of candidates to figure out the optimal combination of data preprocessing steps, machine learning algorithms and hyperparameters. Then, it uses this combination to train an Inference Pipeline, which you can easily deploy either on a real-time endpoint or for batch processing. As usual with Amazon SageMaker, all of this takes place on fully-managed infrastructure.

Last but not least, SageMaker Autopilot also generate Python code showing you exactly how data was preprocessed: not only can you understand what SageMaker Autopilot did, you can also reuse that code for further manual tuning if you're so inclined.

Amazon is emphasizing that SageMaker Autopilot allows inspection of what's happening underneath, unlike with a "black box" set up of other tools.

A detailed tutorial on how to get started with the Autopilot tool can be found further down the page here.

SageMaker Autopilot is now live and available via an Amazon SageMaker subscription, which can be found here.

About the Author

Becky Nagel serves as vice president of AI for 1105 Media specializing in developing media, events and training for companies around AI and generative AI technology. She also regularly writes and reports on AI news, and is the founding editor of PureAI.com. She's the author of "ChatGPT Prompt 101 Guide for Business Users" and other popular AI resources with a real-world business perspective. She regularly speaks, writes and develops content around AI, generative AI and other business tech. Find her on X/Twitter @beckynagel.

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