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Gaining Confidence and Improving Android Developer Workflows as a Software Engineering Intern at Uber

Ankit Agrawal reflects on his internship with Uber Engineering, working on the Developer Experience team to build a feature that would highlight code errors in an IDE.
Zoubin Ghahramani

Science at Uber: Improving Transportation with Artificial Intelligence

Uber Chief Scientist Zoubin Ghahramani explains how artificial intelligence went from academia to real-world applications, and how Uber uses it to make transportation better.
Logan Jeya

Science at Uber: Powering Machine Learning at Uber

Logan Jeya, Product Manager, explains how Uber's machine learning platform, Michelangelo, makes it easy to deploy models that enable data-driven decision making.

Introducing LCA: Loss Change Allocation for Neural Network Training

Uber AI Labs proposes Loss Change Allocation (LCA), a new method that provides a rich window into the neural network training process.

Introducing Cyborg, an Open Source iOS Implementation of Android VectorDrawable

We built Cyborg, an open source implementation of VectorDrawable for iOS, to more easily implement designs across our apps.

Best Practices for Unit Testing in React Version 16

Uber ATG Web Platform intern Anat Kleiman shares her advice for testing React version 16 components when altering application logic.
Flamingoes drinking water

Using GraphQL to Improve Data Hydration in our Customer Care Platform and Beyond

Uber Engineering details how GraphQL integrated into our Customer Care platform, making for more targeted queries and reducing server load.
Building the New Uber Freight App as Lists of Modular, Reusable Components

Building the New Uber Freight App as Lists of Modular, Reusable Components

We redesigned the Uber Freight app with RIBs, our open source plugin architecture, to enable quicker feature rollouts and an improved user experience.

Advancing AI: A Conversation with Jeff Clune, Senior Research Manager at Uber

We sat down with Jeff Clune, Senior Research Manager, to talk about his work in AI, journey to Uber, and Presidential Early Career Achievement in Science and Engineering (PECASE) award.

Science at Uber: Making a Real-world Impact with Data Science

Suzette Puente, Uber Data Science Manager, shares how she applies her graduate work in statistics to forecast traffic patterns and generate better routes.
word cloud

Less is More: Engineering Data Warehouse Efficiency with Minimalist Design

Data science helps Uber determine which tables in a database should be off-boarded to another source to maximize the efficiency of our data warehouse.

Science at Uber: Applying Artificial Intelligence at Uber

Zoubin Ghahramani, Head of Uber AI, discusses how we use artificial intelligence techniques to make our platform more efficient for users.

Migrating Functionality Between Large-scale Production Systems Seamlessly

With zero downtime, Uber's Payments Engineering team embarked on a migration that would allow authorization hold logic to be written once and used across existing and future payments products.

Science at Uber: Powering Uber’s Ridesharing Technologies Through Mapping

Dawn Woodard, Director of Data Science, considers travel time prediction one of Uber's most interesting mapping problems.

Science at Uber: Bringing Research to the Roads

Uber Principal Engineer Waleed Kadous discusses how we assess technologies our teams can leverage to improve the reliability and performance of our platform.

Introducing Uber Poet, an Open Source Mock App Generator for Determining Faster Swift Builds

Uber Poet, an open source mock application generator, helped us determine if refactoring the application part of our code into a few large modules would make our overall Swift build times faster.

Ludwig v0.2 Adds New Features and Other Improvements to its Deep Learning Toolbox

Ludwig version 0.2 integrates with Comet.ml, adds a new serving functionality, and incorporates the BERT text encoder, among other new features.
Fran Bell

Science at Uber: Building a Data Science Platform at Uber

Uber Director of Data Science Franziska Bell discusses how we created data science platforms at Uber, letting employees of all technical skills perform forecasts and analyze data.

Introducing EvoGrad: A Lightweight Library for Gradient-Based Evolution

Uber AI Labs releases EvoGrad, a library for catalyzing gradient-based evolution research, and Evolvability ES, a new meta-learning algorithm enabled by this library.
Chinese Water Dragon photo by InspiredImages/Pixabay

Making Apache Spark Effortless for All of Uber

Uber engineers created uSCS, a Spark-as-a-Service solution that helps manage Apache Spark jobs throughout large organizations.

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