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[Discussion] Building scalable / reproducible ML pipelines

To the more experienced ML professionals in the community – I want to hear about what you use to build scalable ML pipelines at your work. I’ve been building models for a while now for research purposes. However, I’m totally in the dark about the other side of things, namely how to engineer and deploy data/ML pipelines that are scalable and provide reproducible results (whatever that may be in this context).

I’ve looked at scikit-learn pipelines, but they seem a bit clunky while handling pandas dataframes (although workarounds do seem to exist). Another sentiment I hear is that they don’t scale well to large datasets.

Care to part with your wisdom? Thanks!

submitted by /u/G_Balena
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.