Amazon SageMaker is a machine learning service offered by AWS (Amazon Web Services) that provides an integrated development environment for building, training, and deploying machine learning models.

Amazon SageMaker pricing consists of two main components:

1. Notebook Instances: These are used for data exploration, model development, and training. The pricing for notebook instances depends on the instance type and storage you choose. You pay per hour for the instance usage and for any additional storage you use.

2. Training Jobs: When you train your machine learning models on SageMaker, you are charged based on the training time and the instance type used for training. Training job pricing also depends on the volume of data processed during training.

Additionally, there may be costs associated with data storage, data transfer, and inference endpoints if you deploy your models for real-time predictions.

AWS often offers a free tier for SageMaker, allowing you to experiment and explore the service without incurring charges up to certain usage limits.