hands-on-lab-neo4j-and-google and hands-on-lab-neo4j-and-gemini

These are ecosystem siblings representing different generations of the same integration pattern—the first targets Google's general AI/LLM capabilities while the second specifically focuses on their newer Gemini model family.

Maintenance 13/25
Adoption 10/25
Maturity 16/25
Community 22/25
Maintenance 2/25
Adoption 10/25
Maturity 16/25
Community 22/25
Stars: 121
Forks: 51
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 120
Forks: 51
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
No Package No Dependents
Stale 6m No Package No Dependents

About hands-on-lab-neo4j-and-google

neo4j-partners/hands-on-lab-neo4j-and-google

Hands on Lab for Neo4j and Google

This workshop teaches you how to combine graph databases with generative AI to analyze complex datasets. You'll learn to load unstructured data, like SEC filings, into a graph database and then use AI to explore relationships and build chatbots for querying the data. This is ideal for data scientists and data engineers working with large, interconnected datasets, especially in capital markets.

capital-markets financial-analysis data-engineering knowledge-graphs generative-AI

About hands-on-lab-neo4j-and-gemini

neo4j-partners/hands-on-lab-neo4j-and-gemini

Hands on Lab for Neo4j and Google Gemini

This workshop teaches data scientists and data engineers how to build advanced data pipelines and AI applications. You'll learn to extract and load complex data, like SEC filings, into a graph database and then build a chatbot and semantic search over it. The result is a powerful system to explore relationships and gain insights from your data, applicable to fields like capital markets analysis.

data-science data-engineering capital-markets financial-analysis knowledge-graphs

Scores updated daily from GitHub, PyPI, and npm data. How scores work