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Graph-Powered Analytics and Machine Learning with TigerGraph: Driving Business Outcomes with Connected Data - Softcover
Synopsis
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.
You'll explore a three-stage approach to deriving value from connected data: connect, analyze, and learn. Victor Lee, Phuc Kien Nguyen, and Alexander Thomas present real use cases covering several contemporary business needs. By diving into hands-on exercises using TigerGraph Cloud, you'll quickly become proficient at designing and managing advanced analytics and machine learning solutions for your organization.
- Use graph thinking to connect, analyze, and learn from data for advanced analytics and machine learning
- Learn how graph analytics and machine learning can deliver key business insights and outcomes
- Use five core categories of graph algorithms to drive advanced analytics and machine learning
- Deliver a real-time 360-degree view of core business entities, including customer, product, service, supplier, and citizen
- Discover insights from connected data through machine learning and advanced analytics
"synopsis" may belong to another edition of this title.
About the Authors
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.
Phuc Kien Nguyen is a data scientist at ABN Amro Bank in Amsterdam. For the past five years, he has helped develop solutions and machine learning models to combat financial crime. He holds an MSc degree in Information Architecture from Delft University of Technology. Next to his day-to-day job, he writes articles at Medium about data science and network analytics. He has a great passion for storytelling, especially through video games. In his spare time, he loves to play football and catch up with the latest development in technology.
"About this title" may belong to another edition of this title.
- PublisherO'Reilly Media
- Publication date2023
- ISBN 10 1098106652
- ISBN 13 9781098106652
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages314
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Graph-Powered Analytics and Machine Learning with TigerGraph: Driving Business Outcomes with Connected Data
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Paperback. Condition: new. Paperback. 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. You'll explore a three-stage approach to deriving value from connected data: connect, analyze, and learn. Victor Lee, Xinyu Chan, and Gaurav Deshpande from TigerGraph present real use cases covering several contemporary business needs. By diving into hands-on exercises using TigerGraph Cloud, you'll quickly become proficient at designing and managing advanced analytics and machine learning solutions for your organization.Use graph thinking to connect, analyze, and learn from data for advanced analytics and machine learningLearn how graph analytics and machine learning can deliver key business insights and outcomesUse five core categories of graph algorithms to drive advanced analytics and machine learningDeliver a real-time 360-degree view of core business entities, including customer, product, service, supplier, and citizen Discover insights from connected data through machine learning and advanced analytics 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. Phuc Kien Nguyen is a data scientist at ABN Amro Bank in Amsterdam. For the past five years, he has helped develop solutions and machine learning models to combat financial crime. He holds an MSc degree in Information Architecture from Delft University of Technology. Next to his day-to-day job, he writes articles at Medium about data science and network analytics. He has a great passion for storytelling, especially through video games. In his spare time, he loves to play football and catch up with the latest development in technology. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781098106652
Quantity: 1 available
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