{"id":22583013,"url":"https://github.com/andrewwango/neo4j-demos","last_synced_at":"2026-05-20T07:33:42.275Z","repository":{"id":70268815,"uuid":"592798627","full_name":"Andrewwango/neo4j-demos","owner":"Andrewwango","description":"Demonstrating and visualising graph data science and ML using neo4j and GDS with the Northwind and Cora datasets","archived":false,"fork":false,"pushed_at":"2023-02-26T11:03:04.000Z","size":7187,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-03-28T16:45:40.861Z","etag":null,"topics":["cora-dataset","graph-data-science","neo4j","node-classification","northwind-database","tabular-vs-graph"],"latest_commit_sha":null,"homepage":"https://andrewwango.github.io/neo4j-demos/rendered/cora/demo.html","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Andrewwango.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-01-24T15:04:19.000Z","updated_at":"2023-04-11T16:06:25.000Z","dependencies_parsed_at":"2023-05-11T20:00:37.237Z","dependency_job_id":null,"html_url":"https://github.com/Andrewwango/neo4j-demos","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Andrewwango/neo4j-demos","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Andrewwango%2Fneo4j-demos","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Andrewwango%2Fneo4j-demos/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Andrewwango%2Fneo4j-demos/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Andrewwango%2Fneo4j-demos/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Andrewwango","download_url":"https://codeload.github.com/Andrewwango/neo4j-demos/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Andrewwango%2Fneo4j-demos/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266717709,"owners_count":23973384,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-07-23T02:00:09.312Z","response_time":66,"last_error":null,"robots_txt_status":null,"robots_txt_updated_at":null,"robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cora-dataset","graph-data-science","neo4j","node-classification","northwind-database","tabular-vs-graph"],"created_at":"2024-12-08T06:13:14.287Z","updated_at":"2026-05-20T07:33:37.250Z","avatar_url":"https://github.com/Andrewwango.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# neo4j-demos\nThis repo contains notebooks demonstrating and visualising graph data science and ML using [Neo4j](https://neo4j.com/) and [Graph Data Science](https://neo4j.com/docs/graph-data-science/current/introduction/) with the Northwind and Cora datasets.\n\n## Contents\n\n### Cora\n\nThis demo compares classification using a tabular dataset vs using a graph dataset. Using Neo4j and the Graph Data Science libraries, we show that modelling the data using a graph allows us to achieve better classification accuracy!\n\nThe problem studied is classifying a dataset of academic papers into categories using the [Cora dataset](https://paperswithcode.com/dataset/cora). Read the full tutorial here: [\"Comparing ML using tabular vs graph data models with the Cora dataset\"](https://andrewwango.github.io/neo4j-demos/rendered/cora/demo.html).\n\n\u003cp align=\"center\" width=\"100%\"\u003e\n    \u003cimg src=\"cora/assets/cora_overview.png\" width=\"70%\"/\u003e\n\u003c/p\u003e\n\n### Northwind\n\nHere we show how querying a customer-product type of dataset may be easier with a graph data model vs tabular data model. This shows query commands using the [Cypher language](https://neo4j.com/docs/getting-started/current/cypher-intro/) and their equivalents in SQL. We use the [Northwind dataset](https://guides.neo4j.com/northwind/index.html) of customers, products, suppliers and orders.\n\n### Rendered\n\nRendered Quarto blog for Cora demo.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandrewwango%2Fneo4j-demos","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fandrewwango%2Fneo4j-demos","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandrewwango%2Fneo4j-demos/lists"}