<ul><li>Transfer learning is a technique in machine learning that involves using knowledge gained from solving one problem to help solve a different but related problem.</li><li>It allows models to leverage pre-trained neural networks and the experience acquired from solving previous tasks.</li><li>For example, if a neural network has been trained to classify products, it can be used as a starting point for training a new network to classify different types of products.</li><li>Transfer learning is a powerful tool that can save time and computational resources while still achieving high accuracy in new tasks.</li></ul>

How to Use Transfer Learning the Right Way: A Beginner’s Guide

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