Amazon SageMaker Autopilot adds Deep Learning Models
Amazon SageMaker Autopilot, which makes it easy to create highly accurate machine learning (ML) models without requiring any ML expertise, now includes deep learning models, enabling you to quickly and accurately make predictions in a wide variety of deep learning applications.
Amazon SageMaker Autopilot, which makes it easy to create highly accurate machine learning (ML) models without requiring any ML expertise, now includes deep learning models, enabling you to quickly and accurately make predictions in a wide variety of deep learning applications.
Amazon SageMaker Autopilot automatically builds, trains, and tunes the best machine learning model for your structured data, while allowing you to maintain full control and visibility. Starting today, SageMaker Autopilot also uses neural-network based deep learning algorithms to find the best model for your data. Now, you can easily use SageMaker Autopilot to create accurate models for problems with multi-dimensional, multi-class datasets that require deep learning, such as sales forecasting, recommendation systems, call center routing, and advertisement optimization. For example, you can use SageMaker Autopilot to build a model for store sales prediction based on hundreds of complex features such as holiday type, store type, distance from competitors, sales and promotions for each department. SageMaker Autopilot is easy to use, so you can build machine learning models in just a few clicks—without any ML or deep learning expertise.
Deep learning models are now available in Amazon SageMaker Autopilot in all regions where SageMaker Autopilot is available. To get started, visit our documentation and webpage.