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Built image classification deep learning architectures - AlexNet, VGG16, and ResNet using transfer learning and fine-tuning in PyTorch. Final model accuracies achieved are AlexNet-81.2%, VGGNet-85.6%, ResNet-84.7% on 10K test images.

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Built image classification deep learning architectures - AlexNet, VGG16, and ResNet using transfer learning and fine-tuning in PyTorch. Final model accuracies achieved are AlexNet-81.2%, VGGNet-85.6%, ResNet-84.7% on 10K test images.

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Built image classification deep learning architectures - AlexNet, VGG16, and ResNet using transfer learning and fine-tuning in PyTorch. Final model accuracies achieved are AlexNet-81.2%, VGGNet-85.6%, ResNet-84.7% on 10K test images.

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