We built a backtesting service to better assess financial forecast model error rates, facilitating improved forecast performance and decision making.
Uber introduces Hypothesis GU Func, a new extension to Hypothesis, as an open source Python package for unit testing.
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.
Uber's Marketplace simulation platform leverages ML to rapidly prototype and test new product features and hypotheses in a risk-free environment.
We spoke with Fritz Obermeyer and Noah Goodman, Pyro project co-leads, about the potential of open source AI software at Uber and beyond.
Uber built Michelangelo, our machine learning platform, in 2015. Three years later, we reflect our journey to scaling ML at Uber and lessons learned along the way.
Uber developed Michelangelo PyML to run identical copies of machine learning models locally in both real time experiments and large-scale offline prediction jobs.
Uber's Advanced Technologies Group introduces Petastorm, an open source data access library enabling training and evaluation of deep learning models directly from multi-terabyte datasets in Apache Parquet format.
Uber AI Labs introduces Visual Inspector for Neuroevolution (VINE), an open source interactive data visualization tool to help neuroevolution researchers better understand this family of algorithms.
Written in Haskell, Queryparser is Uber Engineering's open source tool for parsing and analyzing SQL queries that makes it easy to identify foreign-key relationships in large data warehouses.
Migrating our Schemaless sharding layer from Python to Go while in production demonstrated that it was possible for us to rewrite the frontend of a massive datastore with zero downtime.
Uber Engineering created Omphalos, our new backtesting framework, to enable efficient and reliable comparison of forecasting models across languages.
Uber Engineering built Denial by DNS, our open source solution for preventing DoS by DNS outages, to facilitate more reliable experiences on Uber's apps, no matter how users choose to access them.
Pyro is an open source probabilistic programming language that unites modern deep learning with Bayesian modeling for a tool-first approach to AI.
Uber Engineering's fraud prevention team built the Mastermind rules engine to detect highly evolved forms of fraud at large scale in a fraction of a second.
Seemingly small inefficiencies are greatly magnified as Uber's business scales. In this article we’ll explore design considerations and unique implementation characteristics of Pyflame, Uber Engineering's high-performance Python profiler implemented in C++.
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