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MLOps and tracking experiments with Allegro AI
Practical AI: Machine Learning, Data Science, LLM
The Challenges of Convincing Data Scientists to Do Things Differently
I think it is a theme that's kind of surging through the community that we need to be more rigorous in terms of the engineering we put into our workflows and AI-driven products. I was wondering from your perspective, what are the sort of main challenges to getting people on board that are currently in data science and AI positions? What are some of those challenges? Is it have to do with this kind of variety of backgrounds that people come from that it's not just engineers or is it more than that?
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