How Uber Uses scikit-learn
7 engineering articles about scikit-learn from Uber's engineering team
Other Uber Technologies
Other Companies Using scikit-learn
Articles
Filter:
The article introduces Orbit, an open-source package designed for Bayesian time series inference and forecasting.
Edwin Ng, Lindsey Elkin, Yifeng Wu, Jing Pan, Ariel Jiang, Steve Yang
10 min read
Has Summary
--
The article discusses the modeling of censored time-to-event data using Pyro, an open-source probabilistic programming language.
Hesen Peng, Fritz Obermeyer
11 min read
Has Summary
--
The article introduces Ludwig, an open-source deep learning toolbox developed by Uber that allows users to train and test deep learning models without writing code.
Piero Molino, Yaroslav Dudin, Sai Sumanth Miryala
13 min read
Has Summary
--
The article discusses Manifold, a model-agnostic visual debugging tool developed by Uber for enhancing machine learning model performance.
Lezhi Li, Tim
14 min read
Has Summary
--
The article introduces Michelangelo PyML, Uber's platform designed for rapid Python machine learning model development.
ApacheApache SparkDockergRPCJavaJSONMachine LearningPySparkPyTorchscikit-learnSQLTensorFlowThriftXGBoost
Kevin Stumpf, Stepan Bedratiuk, Olcay Cirit
15 min read
Has Summary
--
Omphalos is Uber's innovative time series backtesting tool designed to enhance forecasting accuracy and model comparison across various programming languages.
Roy Yang
11 min read
Has Summary
--
The article introduces Michelangelo, Uber's internal machine learning platform designed to democratize machine learning and streamline the process of building, deploying, and operating ML solutions...
Jeremy Hermann, Mike Del Balso
24 min read
Has Summary
--
You've reached the end! All 7 articles loaded.