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Tag: Uber Data

Enabling Collaboration through Open Source: Highlights from Uber Open Summit Sofia 2019

At the Uber Open Summit Sofia 2019, we showcased how open source technologies are driving the future of artificial intelligence, site reliability, and other domains.

Visualizing City Cores with H3, Uber’s Open Source Geospatial Indexing System

In a selection of presentations delivered at a June 2019 Uber meetup, we discuss how to use H3, our open source hexagonal indexing system, to facilitate the granular mining of large geospatial data sets.

Using Causal Inference to Improve the Uber User Experience

Uber Labs leverages causal inference, a statistical method for better understanding the cause of experiment results, to improve our products and operations analysis.

Power On: Accelerating Uber’s Self-Driving Vehicle Development with Data

A key challenge faced by self-driving vehicles comes during interactions with pedestrians. In our development of self-driving vehicles, the Data Engineering and Data Science teams at Uber ATG (Advanced Technologies Group) contribute to the data processing and analysis that help make these interactions safe.

Second Uber Science Symposium: Exploring Advances in Behavioral Science

On May 3, 2019, Uber’s Applied Behavioral Science team hosted the Behavioral Science Track of the Second Uber Science Symposium, featuring a full day of presentations delivered by leading researchers in the field.

Uber Joins Urban Computing Foundation, Contributes Kepler.gl as Organization’s First Hosted Project

In addition to joining the Urban Computing Foundation, Uber is contributing Kepler.gl, an open source geospatial analysis tool, as the organization's first hosted project.

First Uber Science Symposium: Discussing the Next Generation of RL, NLP, ConvAI, and DL

The Uber Science Symposium featured talks from members of the broader scientific community about the the latest innovations in RL, NLP, and other fields.

How Uber Leverages Applied Behavioral Science at Scale

Uber Labs utilizes insights and methodologies from behavioral science to build programs and products that are intuitive and enjoyable for users on our platform.

Manifold: A Model-Agnostic Visual Debugging Tool for Machine Learning at Uber

Uber built Manifold, a model-agnostic visualization tool for ML performance diagnosis and model debugging, to facilitate a more informed and actionable model iteration process.
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Sessionizing Uber Trips in Real Time

Uber's many data flows required modeling the data associated with a specific task, such as a rider trip, into a state machine. The state machine lets engineers focus on just the events needed to successfully accomplish a trip.

Seeing Double: Meet Uber’s Identical Twin Data Scientists

Afshine and Shervine Amidi, identical twins, discuss their journeys to data science and how their work at Uber helps teams improve user experiences on our platform.

Databook: Turning Big Data into Knowledge with Metadata at Uber

Databook, Uber's in-house platform for surfacing and exploring contextual metadata, makes dataset discovery and exploration easier for teams across the company.

H3: Uber’s Hexagonal Hierarchical Spatial Index

Uber developed H3, our open source grid system for optimizing ride pricing and dispatch, to make geospatial data visualization and exploration easier and more efficient.

M4 Forecasting Competition: Introducing a New Hybrid ES-RNN Model

With a solid margin, Uber senior data scientist Slawek Smyl won the M4 Competition with his hybrid Exponential Smoothing-Recurrent Neural Networks (ES-RNN) forecasting method.

From Beautiful Maps to Actionable Insights: Introducing kepler.gl, Uber’s Open Source Geospatial Toolbox

Created by Uber's Visualization team, kepler.gl is an open source data agnostic, high-performance web-based application for large-scale geospatial visualizations.

Growing the Data Visualization Community with deck.gl v5

deck.gl v5 incorporates simplified APIs, scripting support, and framework agnosticism, making the popular open source data visualization software more accessible than ever before.

Mediation Modeling at Uber: Understanding Why Product Changes Work (and Don’t Work)

Uber Labs leverages mediation modeling to better understand the relationship between product updates and their outcomes, leading to improved customer experiences on our platform.

Introducing the Uber AI Residency

Interested in accelerating your career by tackling some of Uber’s most challenging AI problems? Apply for the Uber AI Residency, a research fellowship dedicated to fostering the next generation of AI talent.

Implementing Model-Agnosticism in Uber’s Real-Time Anomaly Detection Platform

Uber Engineering extended our anomaly detection platform's ability to integrate new forecast models, allowing this critical on-call service to scale to meet more complex use cases.

Gleaning Insights from Uber’s Partner Activity Matrix with Genomic Biclustering and Machine Learning

Uber Engineering's partner activity matrix leverages biclustering and machine learning to better understand the diversity of user experiences on our driver app.

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