aws-solutions-library-samples
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guidance-for-training-an-aws-deepracer-model-using-amazon-sagemaker
guidance-for-training-an-aws-deepracer-model-using-amazon-sagemaker PublicDeepRacer workshop content. This Guidance demonstrates how software developers can use an Amazon SageMaker Notebook instance to directly train and evaluate AWS DeepRacer models with full control
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cloud-intelligence-dashboards-framework
cloud-intelligence-dashboards-framework PublicCommand Line Interface tool for Cloud Intelligence Dashboards deployment
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data-lakes-on-aws
data-lakes-on-aws PublicEnterprise-grade, production-hardened, serverless data lake on AWS
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fraud-detection-using-machine-learning
fraud-detection-using-machine-learning PublicSetup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker
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guidance-for-personalized-ecommerce-recommendations-using-amazon-bedrock-agents
guidance-for-personalized-ecommerce-recommendations-using-amazon-bedrock-agents PublicThis Guidance demonstrates how to implement personalized ecommerce recommendations using Amazon Bedrock Agents.
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guidance-for-multi-provider-generative-ai-gateway-on-aws
guidance-for-multi-provider-generative-ai-gateway-on-aws PublicThis Guidance demonstrates how to streamline access to numerous large language models (LLMs) through a unified, industry-standard API gateway based on OpenAI API standards
Repositories
- guidance-for-multi-agent-orchestration-agent-squad-on-aws Public
This Guidance demonstrates how to effectively orchestrate multiple specialized AI agents to solve complex customer support challenges through different coordination mechanisms on AWS. Modern customer service environments demand sophisticated handling of multi-step interactions, personalized responses, and seamless access to various data sources.
aws-solutions-library-samples/guidance-for-multi-agent-orchestration-agent-squad-on-aws’s past year of commit activity - guidance-for-workforce-management-using-amazon-bedrock Public
This Guidance shows how to enhance workforce management through AI-driven automation and real-time intelligence. It demonstrates how to provide staff with quick access to relevant insights, enabling more informed decision-making
aws-solutions-library-samples/guidance-for-workforce-management-using-amazon-bedrock’s past year of commit activity - guidance-for-asynchronous-inference-with-stable-diffusion-on-aws Public
Stable Diffusion is a popular Open Source project for generating images using Gen AI. Building a scalable and cost efficient inference solution is a common challenge. This project shows how to use AWS serverless and container services to build an end-to-end scalable, secure and price effecient asynchronous image generation architecture.
aws-solutions-library-samples/guidance-for-asynchronous-inference-with-stable-diffusion-on-aws’s past year of commit activity - guidance-for-investment-analysis-using-amazon-bedrock Public
This Guidance demonstrates how Amazon Bedrock, with offers a range of large language models (LLMs), can perform generative AI-powered analysis on structured and unstructured data sets to support investment analysts.
aws-solutions-library-samples/guidance-for-investment-analysis-using-amazon-bedrock’s past year of commit activity - cloud-intelligence-dashboards-framework Public
Command Line Interface tool for Cloud Intelligence Dashboards deployment
aws-solutions-library-samples/cloud-intelligence-dashboards-framework’s past year of commit activity - guidance-for-claude-code-with-amazon-bedrock Public
This Guidance demonstrates how organizations can implement secure enterprise authentication for Amazon Bedrock using industry-standard protocols and AWS services
aws-solutions-library-samples/guidance-for-claude-code-with-amazon-bedrock’s past year of commit activity - accelerated-intelligent-document-processing-on-aws Public
This Guidance demonstrates a scalable, serverless approach for automated document processing and information extraction using AWS services, such as Amazon Bedrock Data Automation and Amazon Bedrock foundational models. It combines generative AI and optical character recognition (OCR) to process documents at scale.
aws-solutions-library-samples/accelerated-intelligent-document-processing-on-aws’s past year of commit activity - guidance-for-processing-overhead-imagery-on-aws Public
This Guidance demonstrates how to process remote sensing imagery using machine learning models that automatically detect and identify objects collected from satellites, unmanned aerial vehicles, and other remote sensing devices
aws-solutions-library-samples/guidance-for-processing-overhead-imagery-on-aws’s past year of commit activity - guidance-for-patient-entity-resolution-with-aws-healthlake Public
AWS HealthLake patient matching with AWS Entity Resolution.This Guidance shows how to use AWS Entity Resolution to perform patient entity resolution on healthcare data stored in AWS HealthLake.
aws-solutions-library-samples/guidance-for-patient-entity-resolution-with-aws-healthlake’s past year of commit activity - guidance-for-media-provenance-with-c2pa-on-aws Public
This Guidance demonstrates how to run the Coalition for Content Provenance and Authenticity (C2PA) standard for tracking provenance with media workloads on AWS.
aws-solutions-library-samples/guidance-for-media-provenance-with-c2pa-on-aws’s past year of commit activity
