SERVICE DOMAIN
AI / ML Artificial Intelligence
Build generative AI and machine learning capabilities.PUBLIC NOTES
Knowledge Notes
AI / ML Core Concepts
First separate AI, ML, deep learning, and generative AI, then decide whether the task is training or inference.
→Amazon Bedrock
Use foundation models through managed APIs to build generative-AI applications without managing model infrastructure.
→Amazon Comprehend
Use natural-language processing to identify sentiment, entities, key phrases, language, and topics in text.
→Amazon Kendra
An intelligent enterprise-search service that returns relevant answers and documents across knowledge sources.
→Amazon Lex
A managed service for text and voice conversational interfaces, chatbots, and contact-center bots.
→Amazon Personalize
A managed service that creates personalized recommendations and ranking from users, items, and interactions.
→Amazon Polly
A managed text-to-speech service that turns text into natural-sounding speech.
→Amazon Q Business and Developer
Amazon Q Business is an enterprise knowledge assistant; Amazon Q Developer supports software development and AWS workflows.
→Amazon Rekognition
Analyze objects, scenes, text, faces, and unsafe content in images and video with pretrained capabilities.
→Amazon SageMaker JumpStart
Discover, deploy, and fine-tune pretrained models and solution templates quickly inside SageMaker.
→Amazon SageMaker
A managed platform to prepare data and build, train, deploy, and monitor custom machine-learning models.
→Amazon Textract
Extract text, tables, form fields, and structured data from scanned documents.
→Amazon Transcribe
An automatic speech-recognition service that converts audio and speech into text.
→Amazon Translate
A neural machine-translation service for translating text between languages.
→AWS AI/ML Three-Layer Stack
Choose among pretrained AI services, ML platforms, and ML infrastructure based on control and operational burden.
→TOPIC INDEX