Consider following text and answer quiz questions about it, only include correct answer and no explanation.
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And this brings us to something that’s a little unsettling about artificial neural networks. Imagine a skilled talent scout who’s looking for the next great baseball player. “I’ll know him when I see him,” they might say. They can’t explain how they’ll know, they just will. In the same way, our neural network can’t explain why certain factors are important. Sure, we can look at the values attached to each weight and bias, but the relevance of a number that’s the result of a connection of a connection of a connection will be lost to us.
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So just like how the mind of the talent scout is a black box, so is our neural network. Because we don’t observe the layers between the input and output, they’re referred to as hidden layers.
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True or false: The values of weights and biases in a trained neural network usually have an obvious connection to the inputs.
A. True
B. False The words with all capital letters should appear at least 13 times.
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