Uber Tech Day Machine Learning

Uber Tech Day Machine Learning Information Guide

1. Introduction to Uber Tech Day Machine Learning
2. Main Features
3. Developments
4. Detailed Analysis
5. Summary

Introduction to Uber Tech Day Machine Learning

Yiren Lu, a New York City-based software engineer on Recorded live at the MLOps World GenAI Summit 2025 — Austin, TX (October 8, 2025) Session Title: Michelangelo ( Accurate and reliable ETAs (Estimated Time of Arrival) are central to a seamless and enjoyable rider experience. In this talk, data ... From the MLOps World GenAI Summit 2025 — Virtual Session (October 7, 2025) Session Title: Episode 64 of the Stanford MLSys Seminar Series! DeepETA: How Universal Query Language (UQL) is a unified schema language that helps tie multiple data storage

Collaboration is key when it comes to successful product launches. In this presentation, product marketing manager Kristen ...

Main Features

Developments

Uber Tech Day: Advanced Technology in Risk Management

Uber Tech Day: What's My ETA? The Billion Dollar Question

Uber Tech Day: Global Access to Opportunity with Uber

Uber’s Multi-Agent SDK | Jamieson Leibovitch, Uber

Uber Tech Day: Applied AI In Financial Forecasting

Uber Tech Day: COTA -- Improving Uber Customer Care with NLP, ML, & DL

How Uber Predicts Arrival Times - Xinyu Hu and Olcay Cirit | Stanford MLSys #64

Uber Tech Day: UQL Schema

Uber Tech Day: We're Better Together

Detailed Analysis

Data is compiled from public records and verified media reports.

Last Updated: June 8, 2026

Summary

Disclaimer: Disclaimer: Details estimates are based on publicly available data, media reports, and financial analysis. Actual numbers may vary.