Fine tuning is the process of making small adjustments to achieve the desired output or performance. In deep learning, it involves the use of weights of a trained neural network to program another deep learning algorithm from the same domain. The weights connect each neuron in one layer to every neuron in the next layer in the neural network. Fine tuning is used to speed up the training and/or overcome a small dataset as it already contains vital information from a pre-existing deep learning algorithm.
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