Data Science Industry Applications 2021
Graph AI
Thursday, August 19, 2021
Improving Cyber Threat Detection with Machine Learning, Visualizations and Graph Analytics
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Key Takeaways:
The sophistication of cyber criminals is increasing relentlessly. Accenture found that 68% of business leaders feel their cybersecurity risks are increasing. More and better technologies are required to detect attacks and prevent them, we’ll discuss:
- How graph analytics, machine learning, and visualizations, can directly assist in the identification of threats in your environment.
- Using the same approach as many other security tools, we examine how TigerGraph can help you identify threats earlier along the kill chain of the MITRE Attack Framework.
Friday, August 20, 2021
Smarter AI With Analytical Graph Databases - Best Practices and Case Studies 🐯
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Today's analytical graph databases are taking organizations to another level by connecting all their data, representing knowledge better, and obtaining answers to deeper questions in real-time. These benefits extend to the world of machine learning and AI.
This talk will illustrate several ways in which graph databases and graph analytics can deliver smarter AI:
- Unsupervised learning with graph algorithms
- Feature extraction and enrichment with graph patterns
- In-database ML techniques for graphs
Join us as we share client case studies from 7 out of the top 1 banks in the world, China Mobile, Xandr (part of AT&T), UnitedHealth Group, Jaguar Land Rover and Intuit Corporation. We will cover use cases including entity resolution, customer 36, recommendations, and real-time fraud detection.