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Practical AI Practical AI #66

Build custom ML tools with Streamlit

Streamlit recently burst onto the scene with their intuitive, open source solution for building custom ML/AI tools. It allows data scientists and ML engineers to rapidly build internal or external UIs without spending time on frontend development. In this episode, Adrien Treuille joins us to discuss ML/AI app development in general and Streamlit. We talk about the practicalities of working with Streamlit along with its seemingly instant adoption by AI2, Stripe, Stitch Fix, Uber, and Twitter.

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The Changelog The Changelog #330

source{d} turns code into actionable insights

Adam caught up with Francesc Campoy at KubeCon + CloudNativeCon 2018 in Seattle, WA to talk about the work he’s doing at Source{d} to apply Machine Learning to source code, and turn that codebase into actionable insights. It’s a movement they’re driving called Machine Learning on Code. They talked through their open source products, how they work, what types of insights can be gained, and they also talked through the code analysis Francesc did on the Kubernetes code base. This is as close as you get to the bleeding edge and we’re very interested to see where this goes.

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