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GraphTalk2019

Resources and additional information for my talk on the 2019 Neo4j Summer Conference about Graph Data Modelling

Resources

More Graph Use Cases (login needed, but worth it)

https://neo4j.com/sandbox-v2/

Link to the presentation

https://docs.google.com/presentation/d/1Uab3PTMpjxC85lys3iX831uNefGETYVNAhu0QHOTUFQ/edit?usp=sharing

Kaggle Challenge were I used a graph based approach

PART 1

https://www.kaggle.com/ironben/rdbs-to-graphdb-neo4j-network-approach

PART 2

https://www.kaggle.com/ironben/networkbased-eda-nlp-rec-engine

Developer tools to start to use the power of graphs

GRANDStack:

GraphQL -> to have a one-endpoint API for you database

https://graphql.org/learn/

React -> frontend

https://reactjs.org/docs/getting-started.html

Apollo -> backend

https://www.apollographql.com/docs/

Neo4j -> the database itself

https://neo4j.com/developer/

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Python ->

Start: https://www.datacamp.com/courses/intro-to-python-for-data-science?utm_source=adwords_ppc&utm_campaignid=1242944157&utm_adgroupid=53325797735&utm_device=c&utm_keyword=%2Bdatacamp%20%2Bpython&utm_matchtype=b&utm_network=g&utm_adpostion=1t1&utm_creative=258012599512&utm_targetid=kwd-414126611260&utm_loc_interest_ms=&utm_loc_physical_ms=9063087&gclid=EAIaIQobChMIh9GE0pLn4gIVi08YCh1p6Q3uEAAYASABEgLkQfD_BwE

Neo4j Driver: https://neo4j.com/docs/api/python-driver/current/

Vizualisation:

Gephi -> Open Source Graph Viz Tool (scientific oriented)

https://gephi.org/

You can stream the data with the apoc.gephi.add function from Neo4j to Gephi https://neo4j-contrib.github.io/neo4j-apoc-procedures/#_graphml_import_export

Bloom -> Neo4j Visualisation Tool (business oriented)

https://neo4j.com/bloom/

Linkurios -> Vizualisation Tool (business oriented)

https://linkurio.us/

Libraries and frameworks

https://neo4j.com/developer/tools-graph-visualization/

Contact info

LinkedIn:

https://www.linkedin.com/in/bence-vass-3a882696/

Kaggle:

https://www.kaggle.com/ironben

GitHub:

https://github.com/007vasy/