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Python Deep Learning Projects
book

Python Deep Learning Projects

by Matthew Lamons, Rahul Kumar, Abhishek Nagaraja
October 2018
Intermediate to advanced content levelIntermediate to advanced
472 pages
10h 57m
English
Packt Publishing
Content preview from Python Deep Learning Projects

Pooling

Max pooling can be defined as the process of summarizing a group of values with the maximum value within that group. Similarly, if you computed the average, it would be average pooling. Pooling operations are usually performed on the generated feature maps after convolution to reduce the number of parameters.

Let's take the example array we considered for convolution:

array = np.array([0, 1, 0, 1, 0, 1, 0, 1, 0, 1])

Now, if you were to perform max pooling on this array with the pool size set to size 1*2 and a stride of 2, the result would be an array of [1,1,1,1,1]. The array of size 1*10 has been reduced to a size of 1*5 due to max pooling.

Here, since the pool size is of shape 1*2, you would take the subset of the target array

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Publisher Resources

ISBN: 9781788997096Supplemental Content