newsAWS Machine LearningTrust 88 · LabPublished 1mo agoLive · 1mo ago
Build a unified semantic layer across datasets with multi-dataset Topics in Amazon Quick
In this post, we walk through how multi-dataset Topics work, explain how the chat agent uses defined relationships to generate cross-dataset queries, and demonstrate an end-to-end implementation using a retail analytics scenario in Quick Sight.
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- PossiblePossibly related (embedding) · 49%EKKOLearnAI/hermes-studio →
- PossiblePossibly related (embedding) · 49%huggingface/datasets →
- PossiblePossibly related (embedding) · 48%DataTalksClub/datatalksclub.github.io →
- PossiblePossibly related (embedding) · 47%deepset-ai/haystack-core-integrations →
- PossiblePossibly related (embedding) · 47%stackitcloud/rag-template →
- PossiblePossibly related (embedding) · 50%Demonstrating TOFFEE: A Learned System for Synthesizing Data Agent Trajectories at Scale →
- PossiblePossibly related (embedding) · 52%KudoAI/amazongpt →
- PossiblePossibly related (embedding) · 45%jonathanwvd/awesome-industrial-datasets →
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repotaovietducofficial/ITLR-Fullstack-Recommender-RAGpaperDemonstrating TOFFEE: A Learned System for Synthesizing Data Agent Trajectories at ScalepaperAn Agentic Approach for Active Data Collection, Travel Behavior Modeling, and Weather-Sensitive Demand PredictionrepoDataTalksClub/datatalksclub.github.iorepodeepset-ai/haystack-core-integrationsrepojonathanwvd/awesome-industrial-datasetsrepohuggingface/datasetsrepoKudoAI/amazongptrepostackitcloud/rag-templaterepoEKKOLearnAI/hermes-studio
