Uber uses machine learning (ML) models to power critical business decisions. An ML model goes through many experiment iterations before making it to production. During the experimentation phase, data scientists or machine learning engineers explore adding features, tuning parameters, …
Michelangelo, Uber’s machine learning (ML) platform, powers machine learning model training across various use cases at Uber, such as forecasting rider demand, fraud detection, food discovery and recommendation for Uber Eats, and improving the accuracy of …
Michelangelo, Uber’s machine learning (ML) platform, supports the training and serving of thousands of models in production across the company. Designed to cover the end-to-end ML workflow, the system currently supports classical machine learning, time series forecasting, and deep …