The components of these systems can have their characteristics updated according to the Kohonen rule. François Chollet developed the Keras library to interface with these systems. One type of these systems is characterized by the hyperparameters of depth, stride, and padding, and contains dropout and pooling components. That type of these systems involves smoothing adjacent pixels by (*) convolving them together. The gradient of the loss function is updated in a dynamic programming algorithm for these systems called backpropagation. ReLu is an example of a nonlinear activation function used by the nodes of these systems, which are called “deep” if they have multiple layers. For 10 points, identify these machine learning constructs named for mimicking the human brain. ■END■
ANSWER: artificial neural networks [or neural nets or ANNs; accept convolutional neural networks or CNNs; accept deep neural networks; prompt on deep learning models or machine learning models or ML models or equivalents]
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