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AlexNet is one of the popular variants of the convolutional neural network and used as a deep learning framework.

In this article, we will employ the AlexNet model provided by the PyTorch as a transfer learning framework with pre-trained ImageNet weights. The network will be trained on the CIFAR-10 dataset for a multi-class image classification problem and finally, we will analyze its classification accuracy when tested on the unseen test images. Our aim is to compare the performance of the AlexNet model when it is used as a transfer learning framework and when not used as a transfer learning framework.

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