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This document provides instructions for homework assignments involving Gaussian process classification and neural networks. It includes details on binary Gaussian process classification using different kernels and feature representations on a pedestrian detection dataset. It also describes fitting two-layer neural networks to classify two-dimensional toy datasets, exploring the effects of different numbers of hidden units and random initializations. Finally, it examines maximum margin separating hyperplanes

Author

adithya604

Language

EN