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No Coding Required: Training Models with Ludwig, Uber’s Open Source Deep Learning Toolbox

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No Coding Required: Training Models with Ludwig, Uber’s Open Source Deep Learning Toolbox
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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:

Interested in learning more about Ludwig and AI at Uber? Check out the Ludwig repo and keep up-to-date with other projects Uber AI by subscribing to the Uber Engineering Newsletter!

Special thanks to Piero Molino, Wayne Cunningham, Stan Yee, Seamus Strahan-Malik, Deidre Locklear, Robert Brent Wilson, Blake Henderson, and Doug Rae for their contributions to this video.

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No Coding Required: Training Models with Ludwig, Uber’s Open Source Deep Learning Toolbox
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No Coding Required: Training Models with Ludwig, Uber’s Open Source Deep Learning Toolbox

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