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Dog vs Cat Classification Model using Transfer Learning

Transfer Learning

Transfer learning is a machine learning method where a model developed for a task is reused as the starting point for a model on a second task. We use a pretrained model which is trained for one task. This model can be retrained for a similar task with a smaller dataset.

Transfer Learning gives higher accuracy compared to training models from scratch

Examples:

  1. VGG-16 - Image Recognition model
  2. ResNet-50
  3. Inceptionv3
  4. MobileNet V2

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Dog vs Cat Classification model trained over MobileNetv2. The model is trained on 2000 images and gives an accuracy of 98.75%

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