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Transfer learning is popular in image classification and NLP. It involves retraining a pre-trained model for a new problem, such as classifying flowers. Using a Mobilenet pre-trained model from Google's Tensorflow hub, we can achieve high accuracy with only a few epochs, rather than many. This saves time and computation power as pre-trained models are often trained on millions of images, making training from scratch on a personal computer impractical.
