Wednesday, June 15 - 6:30 PM to 8:30 PM EDT
Data Science & Business Intelligence Society of Atlanta
Roam
3101 Cobb Pkwy SE, Suite 124
Atlanta, GA
Today's analytical graph databases are taking organizations to another level by connecting their data, better representing knowledge, and obtaining answers to deeper questions in real-time. These benefits extend to the world of machine learning and AI.
Join us for a session, where we will demonstrate several different approaches to machine learning with graph data. You can follow along while we cover the following:
- Unsupervised learning with graph algorithms
- Feature extraction and graph enrichment
- External training and integrated solutions with notebooks
- In-database ML techniques for graphs
- In addition, we will review datasets for multiple industries across various graph use cases, like fraud detection, Anti-money Laundering (AML), and recommendation engine.
Not required but attendees should have a high-level understanding of supervised and unsupervised machine learning. Graph database or analytics experience is not necessary.
Important to know : We normally use the first 30 min to socialize a bit and will start the presentation promptly at 6pm. All are welcome to attend.