Graph + AI World - Graph Algorithms for ML

Introduction to Graph Algorithms for Machine Learning Certification

Graph + AI World Session - Recorded September 2020

Graph algorithms are essential building blocks for analyzing your connected data and for conducting machine learning to gain deeper insights from that data. Graph algorithms can be used directly as unsupervised learning, or to enrich training sets for supervised learning. In this session, we will provide an overview of TigerGraph's new training and certification program for Graph Algorithms for Machine Learning: content overview, video and demo format, and the certification process.

About TigerGraph

TigerGraph is the only scalable graph database for the enterprise. Based on the industry’s first Native and Parallel Graph technology, TigerGraph unleashes the power of interconnected data, offering organizations deeper insights and better outcomes. TigerGraph fulfills the true promise and benefits of the graph platform by tackling the toughest data challenges in real time, no matter how large or complex the dataset. TigerGraph’s proven technology supports applications such as fraud detection, customer 360, MDM, IoT, AI and machine learning to make sense of ever-changing big data, and is used by customers including Amgen, China Mobile, Intuit, Wish and Zillow, along with some of the world’s largest healthcare, entertainment and financial institutions.

Graph + AI World:

Introduction to Graph Algorithms for Machine Learning Certification

Graph + AI World Session - Recorded September 2020

Watch the Session

“TigerGraph is highly configurable ands can fit your specific use case. Whether you’re trying to get super fast query times or run heavy graph processing algorithms, setting the right configuration on your cluster will make all the difference.”

Xandr

About TigerGraph