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The video discusses fine-tuning in artificial neural networks, which is closely related to transfer learning. Transfer learning involves using knowledge gained from solving one problem and applying it to a new, related problem. Fine-tuning is the process of taking a model already trained for a task and adjusting it to perform a similar task. Using a pre-trained neural network allows us to leverage what the model has already learned without starting from scratch when building a new model.
