ML for FinServ : Hands-on Lab with Neo4j & AWS Sagemaker

As you know, today’s forward-looking financial services (FinServ) organizations are increasingly turning to artificial intelligence (AI) and machine learning (ML) to solve problems, create opportunities, and improve core processes like fraud detection, claims processing, improved customer visibility, and regulatory filing. We’d like to invite you to this hands-on lab designed specifically for data scientists and engineers, where you’ll get to learn how to apply Neo4j’s graph feature engineering and AWS Sagemaker to your own datasets to resolve the data challenges facing your organization. We’ll walk through deploying Neo4j and Sagemaker on your AWS Account and build a machine learning pipeline with a real-world dataset powered by Neo4j Graph Data Science to improve predictions in Sagemaker. This workshop will empower you to:

• Load data from AWS into Neo4j’s leading graph database
• Utilize the Cypher query language to explore relationships and analyze data
• Create a graph using data science for export to Sagemaker and show the power of predictable algorithms

If you are a data science practitioner in capital markets or any other sector of financial services, this is a session you won’t want to miss!

Looking forward to seeing you at the event!

Ben Lackey
Director Global Cloud Channel Architecture, Neo4j

Ben leads the partner architecture team at Neo4j, working closely with our cloud partners to build better together solutions, making it easier for our customers to quickly get value from Neo4j on AWS. He has a Masters degree in Statistical Learning Theory. During his career he’s worked on everything from original work in polychotomous support vector machines to real time bond pricing systems.