AI/ML on AWS: An Overview
Explore the AWS AI/ML stack, from pre-built AI services and managed ML platforms to foundational ML frameworks and infrastructure, designed to solve diverse business challenges and drive innovation.
Explore the AWS AI/ML stack, from pre-built AI services and managed ML platforms to foundational ML frameworks and infrastructure, designed to solve diverse business challenges and drive innovation.
Amazon Comprehend is a natural language processing service that extracts insights from text documents by analyzing sentiment, key phrases, language, and entities for content understanding and classification.
Amazon GuardDuty provides intelligent threat detection across your AWS infrastructure and resources by continuously monitoring network activity and account metadata.
Amazon Kendra is an intelligent enterprise search service powered by machine learning that delivers precise answers from your content using natural language queries rather than simple keyword matching.
Amazon Macie uses machine learning and automation to discover, classify, and protect sensitive data in Amazon S3, helping organizations maintain data privacy and security compliance.
Amazon Personalize uses machine learning to deliver real-time personalized recommendations based on historical user behavior, enabling customized experiences across applications and content platforms.
Amazon Rekognition enables developers to add visual analysis capabilities to applications through deep learning-based image and video analysis, detecting objects, faces, text, scenes, and activities without requiring machine learning expertise.
Amazon SageMaker is a fully managed platform that enables data scientists and developers to build, train, and deploy ML models at scale without managing underlying infrastructure, featuring a comprehensive MLOps suite and SageMaker JumpStart for accelerated development.
Amazon Textract uses machine learning to automatically extract text, handwriting, and structured data from scanned documents, forms, and tables without manual data entry or custom code.
Focus on Amazon SageMaker, AWS's fully managed platform for building, training, and deploying custom machine learning models at scale with comprehensive MLOps capabilities, offering more control without managing infrastructure.