AWS category
Machine Learning
Generated July 9, 2026
Model building, training, inference, AI services, and ML operations on AWS.
Machine Learning services
34 entries| Service | Category | Production use | Before production | Link |
|---|---|---|---|---|
Choose the right ML services and frameworks to support your work | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Easily implement human review of ML predictions | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Tools, knowledge, and guardrails AI coding agents need to build, deploy, and manage applications on AWS | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Scalable, open-source deep learning framework | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Build internal applications to automate processes and simplify organization activities | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Access best-in-class foundation models to build generative AI applications | Machine Learning | Build production generative AI features with managed foundation models. | Control model access, log prompts safely, evaluate outputs, add guardrails, monitor latency/cost, and protect sensitive data. | Docs |
Deploy and operate agents at scale using any framework and model | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Access the native Anthropic platform with AWS billing and security | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Find your most expensive lines of code | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Discover insights and relationships in text | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Detect and return useful information in unstructured clinical text | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Agentic AI for healthcare that's built around the people that deliver it | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Deep learning on Amazon EC2 | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Docker images for deep learning | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Improve application availability with ML-powered cloud operations | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Increase forecast accuracy using machine learning | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Detect more online fraud faster | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Manage medical imaging data | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Securely store, transform, query, and analyze health data in minutes | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Transform omics data into insights | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Reinvent enterprise search with ML | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Build voice and text chatbots | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Learn about Amazon machine learning services | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Reduce unplanned equipment downtime with predictive maintenance and ML | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
A family of foundation models for Amazon Bedrock | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Build and manage fleets of reliable AI agents to automate UI workflows | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Improve your operations with computer vision at the edge | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Build real-time recommendations into your applications | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Turn text into life-like speech | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Analyze image and video | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Build, train, and deploy machine learning models at scale | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Extract text and data from documents | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Automatic speech recognition | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
Natural and fluent language translation | Machine Learning | Use for model training, inference, feature pipelines, generative AI, and ML operations. | Version datasets/models/prompts, monitor drift/latency/cost, secure model access, review safety, and automate deployment/rollback. | Docs |
No matching service guidance found.