Transfer learning involves utilizing the knowledge of pretrained models to solve new problems. It is used because it requires less computational power and can be trained on a small amount of data, saving time and enhancing learning speed. Examples of transfer learning models include Xception, ResNet, VGG, MobileNet, Efficient Net, and AlexNet.
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Let’s approach this using some simple questions.To gain a deeper understanding…VGGNet-16 Architecture: A Complete GuideSort: