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
- 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 - cloud-intelligence-dashboards-data-collection Public
This Guidance demonstrates how to deploy Cloud Intelligence Dashboards in your AWS environment using AWS CloudFormation templates or command line tools. These pre-built dashboards enable you to drive financial accountability, optimize costs, and track usage goals across their AWS infrastructure.
aws-solutions-library-samples/cloud-intelligence-dashboards-data-collection’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 - guidance-for-building-an-event-driven-sportsbook-on-aws Public
This Guidance demonstrates how to build an event-driven, serverless sportsbook application to help sports betting operators handle spiky, seasonal traffic.
aws-solutions-library-samples/guidance-for-building-an-event-driven-sportsbook-on-aws’s past year of commit activity - guidance-for-scalable-model-inference-and-agentic-ai-on-amazon-eks Public
Comprehensive, scalable ML inference architecture using Amazon EKS, leveraging Graviton processors for cost-effective CPU-based inference and GPU instances for accelerated inference. Guidance provides a complete end-to-end platform for deploying LLMs with agentic AI capabilities, including RAG and MCP
aws-solutions-library-samples/guidance-for-scalable-model-inference-and-agentic-ai-on-amazon-eks’s past year of commit activity - guidance-for-virtual-try-ons-on-aws Public
This Guidance demonstrates how retailers can overcome online shopping limitations by implementing a virtual try-on solution on AWS that allows customers to digitally experience products before purchase.
aws-solutions-library-samples/guidance-for-virtual-try-ons-on-aws’s past year of commit activity - guidance-for-agentic-data-exploration-on-aws Public
This Guidance demonstrates how to overcome data fragmentation challenges by using a team of AI agents to automate the discovery, connection, and analysis of information across siloed systems.
aws-solutions-library-samples/guidance-for-agentic-data-exploration-on-aws’s past year of commit activity - aws-insurancelake-etl Public
This solution helps you deploy ETL processes and data storage resources to create an Insurance Lake using Amazon S3 buckets for storage, AWS Glue for data transformation, and AWS CDK Pipelines. It is originally based on the AWS blog Deploy data lake ETL jobs using CDK Pipelines, and complements the InsuranceLake Infrastructure project
aws-solutions-library-samples/aws-insurancelake-etl’s past year of commit activity - guidance-for-automated-setup-of-aws-transform-for-vmware Public
Automation to help deploy AWS Transform and streamline the setup process by automating the provisioning of required AWS services, network configurations, and security controls.
aws-solutions-library-samples/guidance-for-automated-setup-of-aws-transform-for-vmware’s past year of commit activity
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