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 - Cost_Effective_and_Scalable_Models_Inference_on_AWS_Graviton Public
comprehensive, scalable ML inference architecture using Amazon EKS, leveraging both 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/Cost_Effective_and_Scalable_Models_Inference_on_AWS_Graviton’s past year of commit activity - 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-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 - 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-medialake-on-aws Public
This Guidance demonstrates how to deploy a media lake, which addresses media management challenges for organizations of all sizes using AWS services and partner integrations.
aws-solutions-library-samples/guidance-for-medialake-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 - guidance-for-generative-ai-assistant-on-aws Public
This Guidance shows how to unlock instant insights with a generative AI assistant that transforms content consumption across diverse sources, including web documents, PDFs, media files, and YouTube videos.
aws-solutions-library-samples/guidance-for-generative-ai-assistant-on-aws’s past year of commit activity - guidance-for-protein-language-esm-model-training-with-sagemaker-hyperpod Public
Infrastructure deployment automation of SageMaker HyperPod clusters based on EKS and SLURM orchestration and Protein Language ESM-2 model training job definitions including NVIDIA BioNemo
aws-solutions-library-samples/guidance-for-protein-language-esm-model-training-with-sagemaker-hyperpod’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
