Interview
summary
Claims that machine learning is already replacing hand‑coded decision rules by producing billion auto-generated rules that outperform simple if‑then logic, and that H2O focuses on improving algorithms and the data‑science workflow so nonexperts can ship models. Notes concrete limits: ML handles translation, images, sound, and complex patterns but has no clue what questions to ask about business problems, for example when given a transactions dataset of all card swipes it still needs human-crafted objectives to decide who to deny or reward.
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chapters (5)
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