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Engineering, Data / ML

Enabling Deep Model Explainability with Integrated Gradients at Uber

Uber’s ML platform Michelangelo now supports Integrated Gradients, enabling scalable, interpretable deep model explainability across TensorFlow™ and PyTorch™. Learn how this powers trust, debugging, and decision-making throughout the ML life cycle.

October 23 / Global

Engineering, Data / ML, Uber AI

Requirement Adherence: Boosting Data Labeling Quality Using LLMs

October 21 / Global

Engineering, Data / ML

Rebuilding Uber’s Apache Pinot™ Query Architecture

October 16 / Global

Cadence Workflow Joins the Cloud Native Computing Foundation

October 6 / Global

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Higher Education

Campus chaos, resolved: streamlining event transportation with Vouchers

October 6 / Global

Higher Education

Campus cravings: exploring the top Uber Eats meals at universities

October 3 / Global

Engineering, Mobile

How Uber Standardized Mobile Analytics for Cross-Platform Insights

October 2 / Global

Using Uber: your guide to the Pace RAP Program

October 1 / Global

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Engineering, Data / ML, Uber AIAugust 12 / Global

uReview: Scalable, Trustworthy GenAI for Code Review at Uber

Engineering, Data / ML, Uber AIOctober 21 / Global

Requirement Adherence: Boosting Data Labeling Quality Using LLMs

Engineering, Data / ML, Uber AIAugust 19 / Global

Forecasting Models to Improve Driver Availability at Airports

Engineering, Data / MLOctober 23 / Global

Enabling Deep Model Explainability with Integrated Gradients at Uber

Engineering, Backend, Data / ML, Uber AI

Uber’s Strategy to Upgrading 2M+ Spark Jobs

September 25 / Global

Higher Education

How the University of Illinois streamlines faculty travel with Uber

September 19 / Global

Engineering, Data / ML, Security

Adding Determinism and Safety to Uber IAM Policy Changes

September 18 / Global

Engineering, Backend, Data / ML

Open-Sourcing Starlark Worker: Define Cadence Workflows with Starlark

September 11 / Global

Engineering, Data / ML

Building Uber’s Data Lake: Batch Data Replication Using HiveSync

September 4 / Global

Engineering, Backend

Controlling the Rollout of Large-Scale Monorepo Changes

August 28 / Global

Engineering, Backend

How Uber Serves over 150 Million Reads per Second from Integrated Cache with Stronger Consistency Guarantees

August 26 / Global

Engineering, Backend

Lightweight Office Infrastructure: Transitioning from Backbone to SD-WAN

August 21 / Global

Engineering, Data / ML, Uber AI

Forecasting Models to Improve Driver Availability at Airports

August 19 / Global

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