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EPISODE · Apr 7, 2017 · 15 MIN
[MINI] Backpropagation
from Data Skeptic
Backpropagation is a common algorithm for training a neural network. It works by computing the gradient of each weight with respect to the overall error, and using stochastic gradient descent to iteratively fine tune the weights of the network. In this episode, we compare this concept to finding a location on a map, marble maze games, and golf.
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[MINI] Backpropagation
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How long is this episode of Data Skeptic?
This episode is 15 minutes long.
When was this Data Skeptic episode published?
This episode was published on April 7, 2017.
What is this episode about?
Backpropagation is a common algorithm for training a neural network. It works by computing the gradient of each weight with respect to the overall error, and using stochastic gradient descent to iteratively fine tune the weights of the network. In...
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