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Kumo AI & Relational Deep Learning | Data Brew | Episode 34
Manage episode 445162583 series 2814833
Contenido proporcionado por Databricks. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Databricks o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.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.
33 episodios
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Manage episode 445162583 series 2814833
Contenido proporcionado por Databricks. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Databricks o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.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.
33 episodios
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