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Binary Classification: Understanding Activation and Loss Functions with a PyTorch Exampleby@owlgrey
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Binary Classification: Understanding Activation and Loss Functions with a PyTorch Example

by Dmitrii Matveichev 23mAugust 15th, 2023
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To build a binary classification neural network you need to use the sigmoid activation function on its final layer together with binary cross-entropy loss. The final layer size should be 1. Such a neural network will output a probability p that the input belongs to class 1 and 1-p that the input belongs to class 0.
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