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Home > Data Skeptic > [MINI] Max-pooling
Podcast: Data Skeptic
Episode:

[MINI] Max-pooling
Category: Religion & Spirituality
Duration: 00:12:33
Publish Date: 2017-06-02 10:00:00
Description:

Max-pooling is a procedure in a neural network which has several benefits. It performs dimensionality reduction by taking a collection of neurons and reducing them to a single value for future layers to receive as input. It can also prevent overfitting, since it takes a large set of inputs and admits only one value, making it harder to memorize the input. In this episode, we discuss the intuitive interpretation of max-pooling and why it's more common than mean-pooling or (theoretically) quartile-pooling.
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