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Anne Holler

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Anne Holler is a former staff TLM for machine learning framework on Uber's Machine Learning Platform team. She was based in Sunnyvale, CA. She worked on ML model representation and management, along with training and offline serving reliability, scalability, and tuning.

Engineering Blog Articles

Tuning Model Performance

Introduction

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,

Productionizing Distributed XGBoost to Train Deep Tree Models with Large Data Sets at Uber

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

Evolving Michelangelo Model Representation for Flexibility at Scale

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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

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