Graph Neural Networks (GNNs) is a type of neural network that operates on a graph data structure. It tends to outperform other machine learning techniques when there are well-defined relationships between data as it directly models the connectivities of your graph data. Recently, GNN has gained increasing popularity and has proven its success across various domains including, recommender systems, social networks, demand forecasting, etc.
TigerGraph’s new Machine Learning (ML) Workbench is a Jupyter-based Python development framework that enables data scientists to quickly build powerful deep learning AI models using connected data.
This recording includes:
- An overview of GNN, its applications, and benefits
- Demo of ML Workbench
[Tuesday, March 22nd] How To Navigate Graph Data Science: A Roadmap
Come join Dr. Victor Lee to learn how you can get started with graphs and develop the right mental model for thinking in and using graphs.
[Wednesday, March 23rd] GSQL Schema Design & Query Writing Best Practices: Part 2
Access Part 1 Recording Here
GSQL is a user-friendly, highly expressive, and Turing-complete graph query language. Although learning GSQL is relatively easy, it can be challenging for some users to know where to start when writing a query.
In this session you will learn how to:
- Design a traversal plan with optimal complexity
- Make your queries memory efficient
- Identify the performance bottleneck
- How to choose the right accumulator
- Learn the MPP query execution mechanisms
[Wednesday, March 30th] Connect the Dots in Complex Distributed Data
How to Use Graph Databases for Better Analytics and Faster Business Insights
Attend this webinar and you will discover how to:
- Use graph technologies to rapidly analyze thousands of data sources with millions or billions of elements.
- Answer complex questions about relationships in large data sets.
- Increase speed of queries, improve business outcomes, and save money.
Office Hours - Million Dollar Challenge
Every Tuesday at 7:00 am Paciﬁc and Thursday at 6:00 pm Paciﬁc from February 10 to April 14th
Talk directly with our engineers every week on Discord. During our online ofﬁce hours, you get answers to any questions pertaining to your Graph for All Challenge project, graph modeling, GSQL programming, and more.
Trending Data Sets
NCAAM March Madness scores 1985-2021
Year, round, score, & seed data for NCAAM march madness games, 1985-2021
Fitbits, Field-Tests, and Grades
The effects of a healthy and physically active lifestyle on academic performance
Million Dollar Challenge
We’ve got a million-dollar question: what can you do with graph? Share your graph solution for a global issue with TigerGraph, for a chance to win one of 15 cash prizes, totaling $1M!
Mark your calendars: Submissions are due by April 20, 2022
To register and learn more, visit
Graph for All Million Dollar Challenge - TigerGraph
Join the DevPost!