The Conference for Machine Learning Innovation

Creating a testing workbench for ML teams using just Python

Session
Join the ML Revolution!
Register until September 15:
✓ Save up to $323
✓ 3 Day Special
✓ Team discount
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Join the ML Revolution!
Register until September 15:
✓ Save up to $323
✓ 3 Day Special
✓ Team discount
Register Now
Join the ML Revolution!
Register until August 18:
✓ Pre-conference workshops for free
✓ Save up to €503
✓ 10 % Team Discount
Register Now
Join the ML Revolution!
Register until August 18:
✓ Pre-conference workshops for free
✓ Save up to €503
✓ 10 % Team Discount
Register Now
Join the ML Revolution!
Until the Conference starts:
✓ Group discount
✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Until the Conference starts:
✓ Group discount
✓ Special discount for freelancers
Register Now

As academic researchers at MIT and Columbia University and as Machine Learning practitioners for the last five years, we have repeatedly struggled to effectively share our research with all our stakeholders for feedback and testing purposes.

For example, while working with lead scientists at DARPA under the US Department of Defense, we had to spend a significant amount of time building interactive apps to quickly gather feedback on our NLP research – audio to text translation, text summarization, etc.

Moreover, the need for apps extends beyond model research evaluation to other steps in the ML project lifecycle. For example, we had to create a gamified data collection app in our project with Microsoft.

However, creating such applications was extremely difficult since we had to learn HTML, CSS, JS. These experiences motivated us to create an open-source project that enables ML teams to create apps in minutes using only Python.

In this talk, we will share this new framework that has been built specifically for Python developers. We will also share how to implement this framework and quickly create a model-assisted data labeling app which is a very frequent requirement of ML teams.

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This Session belongs to the Diese Session gehört zum Programm vom BerlinBerlin program. Take me to the program of . Hier geht es zum Programm von Munich Munich .

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Behind the Tracks