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Consider two neural networks that map a scalar input x to a scalar output y. The first network is shallow and has D = 95 hidden units. The second is deep and has K = 10 layers, each containing D = 5 hidden units. How many parameters does each network have? How many linear regions can each network make? Which would run faster?
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Consider two neural networks that map a scalar input x to a scalar output y. The first network is shallow and
has D = 95 hidden units. The second is deep and has K = 10 layers, each containing D = 5 hidden units. How
many parameters does each network have? How many linear regions can each network make? Which would run
faster?
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