University of Cincinnati Analytics Summit

We are excited to be a premier sponsor of the Analytics Summit 2022!

Learn how to harness the predictive power of relationships with Neo4j’s graph technology by joining us at the conference. Bonus: get $100 off when you register with code NEO100.

Visit the Neo4j booth during the event to:

• Learn how our enterprise-ready graph data platform helps you answer previously intractable questions with integrated analytics, graph native machine learning and AI, and other advanced data science capabilities.
• Chat with our graph database experts
• Register to win some really cool prizes.

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Attend our Session:

Beyond the Noise: Generating Recommendations With Graph Data Science

Traditional approaches to processing data fall short when your data is highly connected, causing insights and predictive signals to get lost in the noise. As a result, leading enterprises are turning to more sophisticated data modeling and machine learning approaches to make decisions that improve enterprise efficiency and put distance between you and the competition.

The bigger your dataset, the more difficult it is to know where to get started. In this session, you’ll hear how to make valuable inferences and predictions based on graph structure from data science expert Zach Blumenfeld.

Join the session to learn how to:

• Use graph-native data science approaches to uncover insights and predictive patterns beyond generic recommendations.
• Take different approaches to graph feature engineering – from queries and algorithms to embeddings.
• Leverage graph features for machine learning to get the insights you need.

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Speaker:

Zach Blumenfeld
Data Science Product Specialist, Neo4j

Zach Blumenfeld is a graph enthusiast who helps data scientists, engineers, and business leaders understand and implement Graph Analytics to solve challenging business problems. He has first-hand experience with a wide range of modern-day analytical challenges, including criminal fraud detection, identity resolution, and recommendation systems. Serving in both data science and software developer capacities, Zach has applied graph computing for law enforcement and government entities in support of missions that counter drug trafficking, human smuggling, money laundering, and child exploitation. He has led the development and deployment of full stack graph systems designed to facilitate broad search and analytical query requirements.