Uploaded October 2018 | Updated September 2026, 2 weeks ago
During a September 2018 meetup, software engineer Paul Sorenson offers a peek into Uber’s payment processing systems and the challenges of ensuring payment accuracy.
During a September 2018 meetup, software engineer Paul Sorenson offers a peek into Uber’s payment processing systems and the challenges of ensuring payment accuracy.


![[Uber Seattle] Uber Bus Marketplace Tech Deep Dive
During an April 2019 meetup hosted at Uber’s Seattle office, Uber engineering managers Danny Guo and Eoin OMahony discuss designing algorithms to improve the route generation, fleet positioning and movement, dynamic routes, and walking optimization solutions behind Uber Bus. [Uber Seattle] Uber Bus Marketplace Tech Deep Dive](https://i.ytimg.com/vi/MvWXSK-Rslg/mqdefault.jpg)

![[WiSDOM] Learning Values and Policies from Observation
On October 24, 2019, the WiSDOM (Women in Statistics, Data, Optimization, and Machine Learning) Employee Resource Group hosted the second annual Moving The World With Data meetup, welcoming hundreds of members of the Bay Area tech community to learn about some of our toughest, most interesting data science problems.
In this presentation, Ashley Edwards, a research scientist with Uber AI Labs, shares original work from the machine learning discipline of reinforcement learning. Using examples from the game Coin Run and other simple tasks, she demonstrates how an agent can be made to learn latent policies through observation. She also posed a question: in the future, can we expect robots to learn to act like humans by watching us move?
Learn more about the meetup: https://eng.uber.com/moving-the-world-with-data [WiSDOM] Learning Values and Policies from Observation](https://i.ytimg.com/vi/NZFnIu4U4Aw/mqdefault.jpg)
![[Uber Open Source] Ludwig: A Code-free Deep Learning Toolbox
During this April 2019 meetup in San Francisco, Uber research scientist, Piero Molino introduces Ludwig, a deep learning toolbox that lets people without a machine learning background train prediction models without the need to write code. Ludwig is unique in its ability to help make deep learning easier to understand for non-experts and enable faster model improvement iteration cycles for experienced machine learning developers and researchers alike. By using Ludwig, experts and researchers can simplify the prototyping process and streamline data processing so that they can focus on developing deep learning architectures. [Uber Open Source] Ludwig: A Code-free Deep Learning Toolbox](https://i.ytimg.com/vi/Ns_6Ep7GAIM/mqdefault.jpg)
![[Visualization Nights] Designing Informational Analytics - JD Vogt & Raymon Sutedjo-The
Creating analytics apps and dashboards for business is more than picking the right chart. Its about understanding a users purpose and goals. During our June 2018 Visualization Night, JD Vogt and Raymon Sutedjo-The discuss how the Salesforce Analytics Design team approaches their work and the choices they make when creating analytics experiences, ranging from mapping out users path of inquiry to choosing the right charts and colors. [Visualization Nights] Designing Informational Analytics - JD Vogt & Raymon Sutedjo-The](https://i.ytimg.com/vi/Ntj5Cig68jE/mqdefault.jpg)


![[Uber Open Summit 2018] Using Service Workers for Performance
Service Workers are best known for allowing web applications to work offline, but they can also make your online pages load a lot faster. During Uber Open Summit 2018, engineer Angus Croll presents an overview of Service Workers and demonstrate why theyre your friend if you care about performance. [Uber Open Summit 2018] Using Service Workers for Performance](https://i.ytimg.com/vi/OKUKUMxqlKk/mqdefault.jpg)
![[Uber Open Summit 2018] Using Presto @ Uber
During this Uber Open Summit 2018 tech talk, engineer Zhongting Hu discusses how we leverage Presto in our robust Big Data Platform.
Learn more about Uber Open Source: https://uber.github.io/ [Uber Open Summit 2018] Using Presto @ Uber](https://i.ytimg.com/vi/OXcIgd-0leE/mqdefault.jpg)