Our world is made up of Connected Data that links up to tell a story.
As part of the Neo4j and Google Cloud Alliance, please join us at our upcoming event on "Machine Learning with Graph - Hyper-Personalized Customer Engagement, while Mitigating Risks and Driving Compliance for BFSI."
Date : 25 Apr 2023 (Tue)
Morning Session: 9am to 12pm (Focus on Financial Services)
Venue : Google HK Office: Level 21, Tower 2, Times Square, 1 Matheson St, Causeway Bay, HK, HK-HKG-TW2-21-0-Techtalk Room
Afternoon Session: 2:30pm to 6pm (Hands-on Lab on Neo4j Data Science)
Venue : Google HK Office: Level 25, Tower 2, Times Square, 1 Matheson St, Causeway Bay, HK
During the morning session, we will showcase how Neo4j's graph data science can help you unlock hidden insights from complex data sets, detect patterns, reveal relationships, and uncover insights that might otherwise be missed using traditional data analytics approaches. We will share use cases for financial services in the areas of customer 360, hyper-personalized recommendation, risk mitigation, fraud detection, and AML etc.
In the afternoon session, our hands-on lab is designed for data scientists and engineers. We'll walk you through deploying Neo4j and Vertex AI on the Google Cloud platform, and how to build a machine learning pipeline using real-world data powered by Neo4j Graph Data Science. Please note that you will need to bring your laptop for the session, and the session will not be recorded.
Forward-thinking organizations are increasingly turning to artificial intelligence (AI) and machine learning (ML) to solve problems, create opportunities, and improve their core processes, such as fraud detection, customer analytics, and real-time recommendations.
Join Neo4j and Google experts to learn how to use graph technology to build and deploy accurate and permanent machine learning pipelines that are more scalable than those built on traditional databases.
0900 – 0915 Guest Registration
0915 – 0930 Welcome
0930 – 1045 Introduction to Graph Analytics and Neo4j
1045 – 1100 Break
1100 – 1130 Financial Services Use Case Sharing
1130 – 1145 Google Cloud Platform Marketplace
1145 – 1200 Q&A and Wrap up
1430 – 1500 Welcome
1500 – 1510 Lab 0 - System Check & Verification
1510 – 1525 Lab 1 - Deploying Neo4j
1525 – 1600 Lab 2 - Connecting to Neo4j
1600 – 1625 Lab 3 - Moving Data
1625 – 1640 Break
1640 – 1655 Lab 4 - Exploring Data
1655 – 1720 Lecture/Lab 5 - Graph Data Science
1720 – 1750 Lecture/Lab 6 - Vertex AI
1750 – 1755 Lab 7 - Clean up
1755 – 1800 Questions & Next Steps
Our speakers include:
Mr. Ezhil Vendhan, Graph Technical Expert, Neo4j
Mr. Hubert Ng, Head of APAC Channels and Alliances, Neo4j
Ms. Pauline Yeo, BFSI Practice Lead, BioQuest Advisory
Ms. Annie Poon, ISV Sales, GCR, Google Cloud