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Kumo AI & Relational Deep Learning | Data Brew | Episode 34

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Manage episode 445162583 series 2814833
Content provided by Databricks. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Databricks or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

In this episode, Jure Leskovec, Co-founder of Kumo AI and Professor of Computer Science at Stanford University, discusses Relational Deep Learning (RDL) and its role in automating feature engineering.
Highlights include:
- How RDL enhances predictive modeling.
- Applications in fraud detection and recommendation systems.
- The use of graph neural networks to simplify complex data structures.

  continue reading

43 episodes

Artwork
iconShare
 
Manage episode 445162583 series 2814833
Content provided by Databricks. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Databricks or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

In this episode, Jure Leskovec, Co-founder of Kumo AI and Professor of Computer Science at Stanford University, discusses Relational Deep Learning (RDL) and its role in automating feature engineering.
Highlights include:
- How RDL enhances predictive modeling.
- Applications in fraud detection and recommendation systems.
- The use of graph neural networks to simplify complex data structures.

  continue reading

43 episodes

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