Amazon SageMaker Training
Pricing Details
Pay-as-you-go based on the compute instance time used for training. Pricing depends on the instance type (CPU, GPU) and usage volume. A free tier is available.Features
Scalable model training, distributed training, hyperparameter tuning, managed spot training, support for popular ML frameworks, built-in algorithms, monitoring.Integrations
Deep integration with Amazon S3 (for data), Amazon ECR (for container images), Amazon CloudWatch (for monitoring), and other AWS services. Supports popular ML frameworks.Preview
Amazon SageMaker Training is a fully managed service from Amazon Web Services (AWS) that provides a scalable and distributed environment for training machine learning models. It supports training models built using popular frameworks (TensorFlow, PyTorch, MXNet, and others) as well as SageMaker's built-in algorithms. The service allows easily running training jobs on clusters of compute instances, including GPUs, automatically tuning hyperparameters (Hyperparameter Tuning), and efficiently using resources with managed spot instances. SageMaker Training integrates with other AWS services for data access and model deployment. It is a core component of the SageMaker platform for training models in a production environment.