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(Created page with "==Introduction== Model-centric AI is the paradigm taught in most ML classes and revolves around producing the best model given a clean, well-curated dataset. In contrast, Data-centric AI involves systematically engineering data to build better AI systems. Data-centric AI can come in two forms: *algorithms that understand data and use that information to improve models *algorithms that modify data to improve ML models. Examples of this include curriculum learning (...") |
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