Main Purpose
Amazon SageMaker is a fully-managed service that enables developers and data scientists to build, train, and deploy machine learning models quickly.
Key Features
- Data Labeling and Preparation: SageMaker provides tools to label and prepare data for machine learning models.
- Algorithm Selection: Users can choose from a wide range of built-in algorithms or bring their own custom algorithms.
- Model Training and Tuning: SageMaker simplifies the process of training and tuning machine learning models.
- Model Deployment: Once trained, models can be deployed and scaled automatically using SageMaker.
- Integration with AWS Services: SageMaker integrates with other AWS services such as S3, EC2, and CloudWatch.
Use Case
- Predictive Analytics: SageMaker can be used to build models for advanced analytics on customer data.
- Security Threat Detection: It can also be used for back-end security threat detection.
