
Build, train, and deploy machine learning models at scale on AWS
Amazon SageMaker is a fully managed machine learning platform that covers the entire ML workflow from data preparation to model deployment. It provides developers and data scientists with tools to build, train, and deploy ML models quickly with managed infrastructure, AutoML capabilities, and seamless AWS ecosystem integration.
Web-based IDE for end-to-end ML development with notebooks, debugging, and monitoring tools
Automatically builds, trains, and tunes ML models with full visibility and control
Centralized repository for storing, sharing, and managing ML features across teams
Distributed training with automatic hyperparameter optimization and popular framework support
Deploy models for low-latency predictions or batch processing with serverless options
CI/CD pipelines, Model Monitor for drift detection, and comprehensive experiment tracking
Build models for demand forecasting, churn prediction, and sales optimization using tabular and time-series data
Train and deploy models for medical imaging, manufacturing quality control, and object detection
Monitor transactions in real-time to identify anomalies and prevent fraud at scale
Start using Amazon SageMaker today and boost your productivity.
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Unified platform for building, deploying, and scaling generative AI and ML models