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Convolutional neural networks — Machine Learning Zoomcamp Module 8

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mlz-module-08

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convolutional neural networks (CNN) consist of different types of layers
convolutional layer as filters (i.e. 5 x 5)
dense layers
sliding the filter across the cells of the entire image
calculating similarity scores of the different positions of the filter
creating the feature map, one feature map per filter
chaining layers of simple and complex filters allows the CNN to “learn”
resulting in vector representation of image
activation functions sigmoid for binary classification and softmax for multiclass