TL;DR Every machine learning project produces three core assets: labeled datasets, trained models, and the schemas that define how labels are structured. Most teams manage code with Git, infrastructure with Terraform, and models with… nothing systematic. The result is duplicated work, untraceable training data, models in production that nobody can reproduce, and compliance gaps that […]
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