Ludwig is a code-free deep learning toolbox originally created and open sourced by UberAI. Today, on the podcast the creator of Ludwig Piero Molino and Wes Reisz discuss the project. The two talk about how the project works, its strengths, it’s roadmap, and how it’s being used by companies inside (and outside) of Uber. They wrap by discussing path ahead for Ludwig and how you can get involved with the project.
Why listen to this podcast:
• Uber AI is the research and platform team for everything AI at the company with the exception of self-driving cars. Self-driving cars are left to Uber ATG.
• Ludwig allows you to specify a Tensorflow model in a declarative format that focuses on your inputs and outputs. Ludwig then builds a model that can deal with those types of inputs and outputs without a developer explicitly specifying how that is done.
• Because of Ludwig’s datatype abstraction for inputs and outputs, there is a huge range of applications that can be created. For example, an input could be text and output could be a category. In this case, Ludwig will create a text classifier. An image and text input (such as a question: “Is there a dog in this image”) would output a question answering system. There are many combinations that are possible with Ludwig.
• Uber is using Ludwig for text classification for customer support.
• Datatypes can be extended easily with Ludwig for custom use cases.
• Ludwig would love to have people contribute to the project. There are simple feature requests that are just not prioritized with the current contributor workload. It’s a great place to get involved with machine learning and gain experience with the project.
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