Building the Product Knowledge Graph at Amazon with Luna Dong - #457

Building the Product Knowledge Graph at Amazon with Luna Dong - #457

Today we’re joined by Luna Dong, Sr. Principal Scientist at Amazon. In our conversation with Luna, we explore Amazon’s expansive product knowledge graph, and the various roles that machine learning plays throughout it. We also talk through the differences and synergies between the media and retail product knowledge graph use cases and how ML comes into play in search and recommendation use cases. Finally, we explore the similarities to relational databases and efforts to standardize the product knowledge graphs across the company and broadly in the research community. The complete show notes for this episode can be found at https://twimlai.com/go/457.

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Machine Teaching for Better Machine Learning with Mark Hammond - TWiML Talk #43

Machine Teaching for Better Machine Learning with Mark Hammond - TWiML Talk #43

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Marrying Physics-Based and Data-Driven ML Models with Josh Bloom - TWiML Talk #42

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Data Pipelines at Zymergen with Airflow with Erin Shellman - TWiML Talk #41

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Cognitive Biases in Data Science with Drew Conway - TWiML Talk #39

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Deep Learning for Warehouse Operations with Calvin Seward - TWiML Talk #38

Deep Learning for Warehouse Operations with Calvin Seward - TWiML Talk #38

This week, I’m happy to bring you my interview with Calvin Seward, a research scientist with Berlin, Germany based Zalando. While our American listeners might not know the name Zalando, they’re one of...

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Deep Robotic Learning with Sergey Levine - TWiML Talk #37

Deep Robotic Learning with Sergey Levine - TWiML Talk #37

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17 Juli 201753min

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