AWS Developers | Using AI to Query & Visualize Graph Data with KeyLines @awsdevelopers | Uploaded 3 months ago | Updated 1 hour ago
Welcome to the final video of our Amazon CDK series! In this thrilling conclusion, discover how to use generative AI to query your graph database, including natural language requests, and visualize your data using KeyLines. See your data in a whole new light as we make advanced analytics simple and engaging. Perfect for those looking to take their projects to the next level with cutting-edge Graph and AI technology. Join us and unlock powerful insights today!

Resources:
🎥 Amazon Neptune and LangChain, with Kelvin Lawrence video: youtube.com/watch?v=B7GtC1IeIUA
💡Cambridge Intelligence KeyLines Visualization Tool: cambridge-intelligence.com/neptune?utm_source=aws&utm_medium=blog
🎥 Amazon Q Developer for Visual Studio Code: youtube.com/watch?v=X8pxN8TLQ8o
📝 Code: github.com/build-on-aws/building-a-scooters-graph-including-a-graph-data-generator
📓 Step-by-step blog post: github.com/build-on-aws/building-a-scooters-graph-including-a-graph-data-generator/tree/main/project_blog

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Chapters:
00:00 - Intro to Graphs and Amazon Q Developer
00:36 - Use Amazon Q Developer to assist with Gremlin queries in VS Code
04:07 - Configure Amazon Bedrock and LangChain, to query Amazon Neptune
07:40 - Run Natural Language to query an Amazon Neptune database
10:34 - Cambridge Intelligence KeyLines demo, to visualize Amazon Neptune
15:52 - Video series summary

#amazonq #techtutorial #langchain