Background of Uber Open Source Distributed Deep Uber Open Source Distributed Deep
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In order to build a better version of real-time surge pricing, In this video from the Stanford HPC Conference, Alex Sergeev from
Core Information
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Developments
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Distributed Deep Learning with Horovod on Ray - Travis Addair, Uber
[Uber Open Source] Petastorm: Uber ATG's Data Access Library for Deep Learning -- Yevgeni Litvin
[Uber Open Summit 2018] Building Your Own Metrics Pipeline with M3
Horovod: Distributed Deep Learning for Reliable MLOps at Uber - Travis Addair, Uber Technologies
[Uber Open Source] Profile Spark Applications at Scale -- Bo Yang
[Uber Open Summit 2018] Jaeger: Distributed Tracing at Uber
[Distributed Tracing NYC] Building a DIY Distributed Database in One Weekend
[Uber Open Summit 2018] Tiling the Earth with Hexagons
Deep Dive Into OpenSearch Pull-Based Ingestion at Uber - Varun Bharadwaj, Uber & Yupeng Fu, Uber Inc
[Uber Open Summit 2018] Petastorm: Training & Evaluation of Deep Learning Models
[Uber Open Source] Engineering Sub-City Geos for a Hyper-Local Marketplace with Uber
[Uber Seattle] Horovod: Distributed Deep Learning on Spark
Detailed Analysis
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Last Updated: June 8, 2026
Final Thoughts
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