Amazon SageMaker Automatic Model Tuning is now available through SageMaker Search
Amazon SageMaker Automatic Model Tuning allows you to find the most accurate version of your machine learning model by finding the optimal set of hyperparameter configurations for your dataset. SageMaker Automatic Model Tuning is now integrated with the SageMaker Search API, which lets you quickly find and evaluate the most relevant model tuning jobs from potentially hundreds or thousands of them.
Amazon SageMaker Automatic Model Tuning allows you to find the most accurate version of your machine learning model by finding the optimal set of hyperparameter configurations for your dataset. SageMaker Automatic Model Tuning is now integrated with the SageMaker Search API, which lets you quickly find and evaluate the most relevant model tuning jobs from potentially hundreds or thousands of them.
Starting today, you can quickly organize, track and evaluate your model tuning jobs through SageMaker Search. You now have the flexibility to search your tuning jobs based on multiple attributes, including the hyperparameter job name, current status, last-modified time and the tags you have added to your tuning jobs. You can also compare and sort your tuning jobs based on these attributes. This integration helps you to keep track of the tuning jobs created and quickly find the ones you are looking for, thus accelerating the discovery of the best model.
The integration with the SageMaker Search API is now available for SageMaker Automatic Model Tuning in all commercial AWS Regions. To learn more, please read the SageMaker Search API reference guide and the SageMaker Automatic Model Tuning technical documentation.