Twin4j

This Week in Neo4j: LangChain, BigQuery, New Course for Beginners, RailsGraph, GDS Community Detection, and More

Sr. Manager, Developer Community

June 17, 2023

3 min read

Welcome to this week’s newsletter!
Check out Tomaz Bratanic’s latest blog about integrating graph databases into LLM applications. It covers using graph algorithms like PageRank to provide relevant answers and optimizing prompts for Cypher statement generation to retrieve relevant information. Also recommended is the Neo4j Course for Beginners by freeCodeCamp.org. You’ll learn how to use Neo4j as the backend storage for a real-world application created with Java and Spring Boot and how to create a front-end with React to interact with the data. Also, the latest GraphStuff.FM episode is out. Watch “The Perfect Graph For The Perfect Problem” with Jason Koo, Alison Cossette, Andreas Kollegger and Will Lyons is out.

NODES 2023 is coming up in just a few months on October 26. Join thousands of fellow developers, data scientists, and data engineers to get firsthand knowledge from peers who will show you the ropes! The Call for Papers is open until June 30.

Cheers,

Yolande Poirier

COMING UP NEXT WEEK!

- Graphversation: Causal inference powered by Knowledge Graph for applied security research on June 19, 2023.
- LiveStream: Discovering AuraDB Free with Michael & Alexander on June 19, 2023.
- Graph Meetup: Accenture Israel on June 21, 2023.
- Graph Meetup: How to Create Interconnected Synthetic Data on June 23, 2023.
- All Neo4j Events: Webinar, Live demos, and More.
- GraphSummit Series: Get Connected With Graphs.

FEATURED NODES SPEAKER:
Payel Bhunia

Payel Bhunia is a Senior Software Engineer at ZF Group, India. She has a total of 9 years experience in the IT industry. In her NODES 2022 presentation, she explains how to run Neo4j in Docker and deploy Neo4j applications in OpenShift. Watch her talk!

LANGCHAIN CYPHER SEARCH: Tips & Tricks

Tomaz Bratanic continues to explore use cases for integrating knowledge graphs into LLM and LangChain applications. You will learn how to improve prompts to produce better and more accurate Cypher statements.

AI: Google (PaLM2) Gen AI Bot With Neo4j and BigQuery

Surya Kunju explores the integration of Google’s Generative AI with Neo4j, allowing users to import BigQuery tables. The results can then be written back into GCP and used to design a Q&A bot using PaLM2 using relationships discovered by Graph Data Science.

NEO4J TRAINIG: FreeCodeCamp Beginner Course

Learn how to use Neo4j with Java Spring Boot and React in this course with over 5 hours of instruction taught by freeCodeCamp team members Farhan Chowdhury and Gavin Lon.

ACCELERATE DOMAIN LEARNING: Explore Application Dependencies With RailsGraph

Ahmad Elassuty describes the motivation behind RailsGraph, a Ruby gem that generates an interactive and queryable dependency graph for different entities within a Ruby on Rails application. The gem will parse your application’s Active Record models, Associations, Attributes, etc., and inserts the data into a Neo4j database.

GRAPH ACADEMY: Community Detection With GDS

This course teaches you how to preprocess and explore a dataset in order to complete a user segmentation task based on their survey response. The course covers KMeans, kNN, and The Leiden Algorithm in GDS.