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Understanding softmax and the negative log-likelihood

ljvmiranda921.github.io · 1,188 words · saved by 1 readers

In this notebook I will explain the softmax function, its relationship with the negative log-likelihood, and its derivative when doing the backpropagation al...

In this notebook I will explain the softmax function, its relationship with the negative log-likelihood, and its derivative when doing the backpropagation algorithm. If there are any questions or clarifications, please leave a comment below. Softmax Activation Function Negative log-likelihood (NLL) Derivative of the Softmax Softmax Activation Function The softmax activation function is often placed at the output layer of a neural network. It’s commonly used in multi-class learning problems where a set of features can be related to one-of-\(K\) classes. For example, in the CIFAR-10 image classi

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