interpretability of neural networks
Interpretability of neural networks is the ability to understand and explain how a neural network makes predictions or decisions. It involves uncovering the inner workings of the network, such as the weights and biases of its parameters, in order to gain insights into its decision-making process. This helps to build trust in the predictions of the neural network and enables humans to comprehend and validate its output, thus making it more transparent and accountable.
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