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In this video, we explore fine-tuning and its connection to transfer learning. Transfer learning involves using knowledge from solving one problem to address a related problem. Fine-tuning is a process of adjusting a pre-trained model to perform a similar task. By leveraging a pre-existing neural network, we can utilize previous learning without starting from scratch.