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A comment on Why deep learning works even though it shouldn’t. Parent comment
It's not guaranteed at all. Overcomplicated models will "overfit" the training data and generalize very poorly.
> some curves cannot be expressed as a polynominal
You can approximate any (continuous and blah blah) curve arbitrarily well with Taylor expansions.
In fact, polynomials are one of the the most common examples to demonstrate overfitting. See figure 2 on wikipedia (https://en.wikipedia.org/wiki/Overfitting)
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It's not guaranteed at all. Overcomplicated models will "overfit" the training data and generalize very poorly.
> some curves cannot be expressed as a polynominal
You can approximate any (continuous and blah blah) curve arbitrarily well with Taylor expansions.
In fact, polynomials are one of the the most common examples to demonstrate overfitting. See figure 2 on wikipedia (https://en.wikipedia.org/wiki/Overfitting)