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by hiddencost
4336 days ago
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That's a dangerous way of thinking about ML. Models aren't magic, they're a approximate hacks that end up working for a specific instance of a problem. More data is always nice, but typically you see accuracy level off (diminishing returns). ML is a constant process of improving your data, increasing the amount of available data (not the same as improving your data), improving your features, and improving your model. No one thing is sufficient. |
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