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Machine Learning with Swift

You're reading from   Machine Learning with Swift Artificial Intelligence for iOS

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781787121515
Length 378 pages
Edition 1st Edition
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Authors (3):
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Jojo Moolayil Jojo Moolayil
Author Profile Icon Jojo Moolayil
Jojo Moolayil
Oleksandr Baiev Oleksandr Baiev
Author Profile Icon Oleksandr Baiev
Oleksandr Baiev
Alexander Sosnovshchenko Alexander Sosnovshchenko
Author Profile Icon Alexander Sosnovshchenko
Alexander Sosnovshchenko
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Table of Contents (14) Chapters Close

Preface 1. Getting Started with Machine Learning FREE CHAPTER 2. Classification – Decision Tree Learning 3. K-Nearest Neighbors Classifier 4. K-Means Clustering 5. Association Rule Learning 6. Linear Regression and Gradient Descent 7. Linear Classifier and Logistic Regression 8. Neural Networks 9. Convolutional Neural Networks 10. Natural Language Processing 11. Machine Learning Libraries 12. Optimizing Neural Networks for Mobile Devices 13. Best Practices

Pooling operation


Pooling or subsampling is a simple operation of input size decreasing (Figure 9.2). If you have a black and white image, and you want to decrease its size, you can do it in the following way: chose a sliding window of size × m and stride s. Go through the image, applying sliding window and shifting on the s pixels every time you want to move your window. At each position calculate an average (for average pooling) or maximum (for max pooling) and record this value into the destination matrix. Now, there are two common ways to handle borders of the image:

Figure 9.2. Pooling operation. Grey window in the source image corresponds to the grey cell in the destination image

The pooling is used in the CNNs to reduce the size of the data, as it travels down the network.

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