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Powering the Next-Generation Machine Learning Solution with Graph Analytics on Connected Data with Xilinx and TigerGraph
August 11, 2020 @ 10:00 AM - 11:00 AM
Please join Xilinx and TigerGraph to learn about the next-generation machine learning solution combining cutting edge hardware with graph analytics on connected data to answer these key questions:
- How do I understand the wellness journey of a patient and find patients like them in real-time to figure out the recommended next steps?
- Can I understand a customer’s journey while buying a product or service and find other customers who are on a similar journey in real-time to help them buy a suitable product or service?
- Which groups of users and accounts are connected and appear to be part of a fraud or money laundering ring?
The webinar presents a new machine learning solution for the two key use cases – product or service recommendation engine and fraud detection.
The Xilinx and TigerGraph Product or Service Recommendation Engine and Fraud Detection solutions can be deployed today on AWS EC2 F1 instances, Azure NP VMs (preview), and on Alveo U50 Data Center Accelerator Cards.
TigerGraph is the only scalable graph database for the enterprise and provides in-database machine learning for delivering next-generation solutions for all industries.
Director of Business Development
Dan Eaton is the worldwide business development lead of database and data analytics for the data center group at Xilinx. Prior to joining Xilinx Dan was Director of Enterprise Services at DirectStream and founded Parallel Computing Solutions. Dan holds a bachelor’s degree in mechanical engineering from Iowa State University and an MBA from the University of Minnesota.
Head of Product Strategy and Developer Relations
Dr. Victor Lee brings a strong academic background, decades of industry experience, and a commitment to quality and service to TigerGraph. Victor was a circuit designer and technology transfer manager at Rambus, before returning to school for his computer science PhD, focusing on graph data mining and algorithms. He received his BS in Electrical Engineering and Computer Science from UC Berkeley, MS in Electrical Engineering from Stanford University, and PhD in Computer Science from Kent State University. Before TigerGraph he was a visiting professor at John Carroll University.
Kumar Deepak is a Distinguished Engineer in the Data Center Group (DCG) at Xilinx.He has over 20 years of experience in architecting and developing large-scale complex software and hardware systems.Currently, he is responsible for architecting solutions for accelerating Databases and Database Analytics on Xilinx FPGAs.He received his B.S in Electronics and Communication Engineering from Indian Institute of Technology, Kharagpur.