Amazon SageMaker
Amazon SageMaker is a fully managed machine learning platform from AWS that enables developers and data scientists to build, train, and deploy ML models quickly and at scale. It supports the entire ML lifecycle with integrated tools and infrastructure.
Key Features
Integrated Jupyter Notebooks: Launch notebooks with pre-configured environments and data access.
Built-in + Custom Models: Use built-in algorithms or bring your own models using popular ML frameworks like TensorFlow, PyTorch, and scikit-learn.
Automated Model Tuning: Hyperparameter optimization to improve model performance.
One-Click Deployment: Seamlessly scale models to production with built-in hosting.
MLOps & Monitoring: Tools for model versioning, pipeline automation, and performance tracking.
Example Use Cases
Rapid prototyping and training of ML models
Large-scale deployment of real-time inference APIs
Full-lifecycle ML operations and governance
Integrating AI into enterprise applications on AWS