Graph-Powered Analytics and Machine Learning with TigerGraph - Driving Business Outcomes with Connected Data

"With the rapid rise of graph databases, organizations are now implementing advanced analytics and machine learning solutions to help drive business outcomes. This practical guide shows data scientists, data engineers, architects, and business analysts how to get started with a graph database using TigerGraph, one of the leading graph database models available."--Provided by publisher.

About the author

Victor Lee is Vice President of Machine Learning and AI at TigerGraph. His Ph.D. dissertation was on graph-based similarity and ranking. Dr. Lee has co-authored book chapters on decision trees and dense subgraph discovery. Teaching and training have also been central to his career journey, with activities ranging from developing training materials for chip design to writing the first version of TigerGraph's technical documentation, from teaching 12 years as a full-time or part-time classroom instructor to presenting numerous webinars and in-person workshops.

Product details

• Authors: Xinyu Chang, Victor Lee, Phuc Kien Nguyen, Victor Lee Ph.D.
• Publisher: O'Reilly
• Languages: English
• Product format: Paperback / Softback
• Released: 31.08.2023
• EAN: 9781098106652
• ISBN: 978-1-09-810665-2
• Dimensions: 178 mm x 232 mm x 20 mm
• Weight: 564 g
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; machine learning, COMPUTERS / Data Science / Machine Learning