![[Uber Marketplace] Using Machine Learning to Power Uber Eats Charlie Zhang @UberEngineering](https://i.ytimg.com/vi/XAg4DIgoUdE/maxresdefault.jpg)
Uploaded October 2018 | Updated September 2026, 2 weeks ago
During a May 2018 meetup, engineering manager Charlie Zhang discusses how Uber uses machine learning to create a reliable, affordable, and effortless user experience on the Uber Eats app.
During a May 2018 meetup, engineering manager Charlie Zhang discusses how Uber uses machine learning to create a reliable, affordable, and effortless user experience on the Uber Eats app.
![[Uber Marketplace] Using Machine Learning to Power Uber Eats Charlie Zhang](https://i.ytimg.com/vi/XAg4DIgoUdE/mqdefault.jpg "[Uber Marketplace] Using Machine Learning to Power Uber Eats Charlie Zhang
During a May 2018 meetup, engineering manager Charlie Zhang discusses how Uber uses machine learning to create a reliable, affordable, and effortless user experience on the Uber Eats app.")
![[Uber Open Summit 2018] Closing Keynote with Zoubin Ghahramani, Chief Scientist, Uber](https://i.ytimg.com/vi/YKrXmRuEBeU/mqdefault.jpg "[Uber Open Summit 2018] Closing Keynote with Zoubin Ghahramani, Chief Scientist, Uber
During the closing keynote of Uber Open Summit, Ubers Chief Scientist Zoubin Ghahramani discusses the symbiotic nature of open source collaboration and artificial intelligence, and how Uber is committed to growing our suite of open source ML technologies.")
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At Uber, we use data for nearly everything from influencing policy to building products and gleaning market insights. However, the data alone doesnt always tell the full story. Color, composition, and framing play a critical role in developing a narrative that helps connect emotionally and visually with your audience. During our June 2018 Visualization Night, Uber Principal Designer Erik Klimczak discusses how the Uber Data Design team leverages data throughout the organization to build better products.")
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During Ubers September 2019 Visualization Nights meetup, Uber engineer Ben Kramer and data analyst Utsav Shah walk through how to use the Uber Movement speeds data set with Kepler.gl to visualize insights about San Francisco traffic.")
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During a February 2019 Distributed Tracing NYC meetup, Uber software engineer Joe Farro explores several techniques for deriving value from distributed traces as well as covers the strengths and weaknesses of different distributed tracing approaches and how they relate to one another.
Joe is a software engineer and member of the Observability team at Uber. Hes a core contributor to the Jaeger and OpenTracing CNCF projects.")
![[Destination:Web ] Async Iterators in The Real World](https://i.ytimg.com/vi/ZgYKTAAjC8A/mqdefault.jpg "[Destination:Web ] Async Iterators in The Real World
Adobes Jon Kuperman shares best practices for building accessible web applications. Fortunately, there are several tools you can use to make developing an accessible application a breeze. In this talk, he discusses what accessibility is, why it’s important, how to ensure your app is accessible and how to add automated testing to make sure it stays that way.")
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During this July 2019 meetup at Uber’s New York City office, Andrew Kofink of Red Hat presents strategies for maintaining accessible open source repositories and nurturing positive open source communities.")
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In this August 2018 Distributed Tracing - NYC presentation, Agolo SRE Mahmoud Saada discusses techniques and tips for debugging Kafka pipelines.")
