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The GLA family of logistic networks is a set of models used in statistical analysis for binary classification tasks. These models were developed by Geoffrey Hinton and his colleagues at the University of Toronto and are based on the principle of deep learning.

The GLA family of logistic networks is a group of deep neural networks that can be used for various tasks such as image recognition, speech recognition, and natural language processing. These models are particularly effective for solving classification problems where the inputs are high-dimensional and non-linear.

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