Uploaded June 2019 | Updated September 2026, 2 weeks ago
Machine learning models perform a diversity of tasks at Uber, from improving our maps to streamlining chat communications and even preventing fraud. In addition to serving a variety of use cases, it is important that we make machine learning as accessible as possible for experts and non-experts alike so it can improve areas across our business.
In this spirit, we built Ludwig, an open source, deep learning toolbox built on top of TensorFlow that allows users to train and test machine learning models without writing code.
To explain how this powerful framework works, Piero Molino, Ludwig creator and Uber AI senior research scientist, discusses Ludwig’s origin story, common use cases, and how others can get started with the software.
Learn more about Ludwig by checking out the repo (ludwig.ai) and reading our article about the software on the Uber Engineering Blog: eng.uber.com/introducing-ludwig
Machine learning models perform a diversity of tasks at Uber, from improving our maps to streamlining chat communications and even preventing fraud. In addition to serving a variety of use cases, it is important that we make machine learning as accessible as possible for experts and non-experts alike so it can improve areas across our business.
In this spirit, we built Ludwig, an open source, deep learning toolbox built on top of TensorFlow that allows users to train and test machine learning models without writing code.
To explain how this powerful framework works, Piero Molino, Ludwig creator and Uber AI senior research scientist, discusses Ludwig’s origin story, common use cases, and how others can get started with the software.
Learn more about Ludwig by checking out the repo (ludwig.ai) and reading our article about the software on the Uber Engineering Blog: eng.uber.com/introducing-ludwig
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