Uploaded June 2018 | Updated September 2026, 2 weeks ago
User Signup is the entry point to the Uber Platform. In this presentation, software engineer Molly Long will cover the evolution of rider signups at Uber with respect to Uber’s rapid growth, as well as the various requirements for each market and product.
User Signup is the entry point to the Uber Platform. In this presentation, software engineer Molly Long will cover the evolution of rider signups at Uber with respect to Uber’s rapid growth, as well as the various requirements for each market and product.
![[Uber Open Summit 2018] Building Your Own Metrics Pipeline with M3](https://i.ytimg.com/vi/cHx4DuqINTM/mqdefault.jpg "[Uber Open Summit 2018] Building Your Own Metrics Pipeline with M3
To facilitate the growth of Uber’s global operations, we need to be able to quickly store and access billions of metrics on our back-end systems. As part of our robust and scalable metrics infrastructure, we built M3, an open source metrics platform that has been in use at Uber for several years now. During this talk, engineer Nikunj Aggarwal walks through what a general metrics pipeline looks like and how M3 components can be used for the various stages of the pipeline without locking you in to a particular vendor. He also covers some of the unique challenges we face at Uber’s scale and how the learnings from those can be used by other companies.
Learn more about Uber Open Source: https://uber.github.io/")
![[Uber Marketplace] An Introduction Chintan Turakhia](https://i.ytimg.com/vi/cdNn44JYtNw/mqdefault.jpg "[Uber Marketplace] An Introduction Chintan Turakhia
In this presentation from a May 2018 meetup, engineering manager Chintan Turakhia discusses how the Uber Marketplace leverages machine learning to deliver improved rider, driver, and eater experiences.")
![[XGBoost Meetup] Introduction to the XGBoost Community Nan Zhu & Philip Cho](https://i.ytimg.com/vi/dsqwIRrdcTA/mqdefault.jpg "[XGBoost Meetup] Introduction to the XGBoost Community Nan Zhu & Philip Cho
During a January 2019 XGBoost meetup hosted at Ubers SF office, Uber software engineer Nan Zhu and Amazon software engineer Philip Cho discuss the history and development of XGBoost, an open source software library that provides a gradient boosting framework for C++, Java, Python, R, and Julia.")
![[Uber Open Source] Profile Spark Applications at Scale Bo Yang](https://i.ytimg.com/vi/fCTdbX-mG2I/mqdefault.jpg "[Uber Open Source] Profile Spark Applications at Scale Bo Yang
During a June 2018 Open Source Meetup at our Seattle office, senior software engineer Bo Yang discusses how Ubers open source JVM Profiler enables us to profile Spark applications at scale across our microservices.")
![[Uber Seattle] Horovod: Distributed Deep Learning on Spark](https://i.ytimg.com/vi/fZ9P1v1jtFM/mqdefault.jpg "[Uber Seattle] Horovod: Distributed Deep Learning on Spark
During this April 2019 meetup, Uber engineer Travis Addair introduces the concepts that make Horovod work, and walks through how to make use of Horovod on Spark to add distributed training to machine learning pipelines. Horovod is a distributed training framework for TensorFlow, PyTorch, Keras, and MXNet. Scaling to hundreds of GPUs, Horovod can reduce training time from hours to minutes with just a handful of lines added to existing single-GPU training processes.")
![[WiSDOM] An Intriguing Failing of Convolutional NNs & the CoordConv Solution Rosanne Liu](https://i.ytimg.com/vi/gMGL-shl3P8/mqdefault.jpg "[WiSDOM] An Intriguing Failing of Convolutional NNs & the CoordConv Solution Rosanne Liu
During an October 2018 meetup, Uber WiSDOM (Women in Statistics, Data Optimization, and Machine Learning) member & Uber AI researcher Rosanne Liu discuses how convolutional neural networks often fail to complete seemingly trivial tasks and introduces a novel solution to to improve their performance: the CoordConv layer.")
![[Go NYC] End-to-End Testing with Golang Adrian Witas](https://i.ytimg.com/vi/hfVAXTi39UA/mqdefault.jpg "[Go NYC] End-to-End Testing with Golang Adrian Witas
During an October 2018 Go Language NYC meetup, Adrian Witas, VP Software Architect at Viant, discusses how to conduct end-to-end testing with Go.")
![[Uber Mobility] Profiler Performance - Brian Attwell](https://i.ytimg.com/vi/ime9EBuvxDA/mqdefault.jpg "[Uber Mobility] Profiler Performance - Brian Attwell
In this presentation during a March 2018 meetup, staff engineer Brian Attwell introduces Nanoscope, a method tracing tool for Android that improves app performance.
Read the Eng Blog article: https://eng.uber.com/nanoscope/")
