Advanced Analytics and Machine Learning on Connected Data

 RECORDED MaRch 16, 2022

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.

Attend this webinar and learn about:

  1. Overview of GNN, its applications, and benefits
  2. Demo of ML Workbench

Presenter: Andrew Wei, TigerGraph