Fine-tuning CNN
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Fine-tuning a CNN involves adjusting the pre-trained model's weights to fit the new task. This can be done by training the model on the new task's data. In this problem, we will fine-tune a pre-trained CNN to classify images.
Example:
We have a pre-trained model that can classify images into 1000 categories. We want to fine-tune this model to classify images into 10 categories.
Constraints:
Test Cases
Test Case 1
Input:
[VGG16(weights='imagenet', include_top=False, input_shape=(224, 224, 3)), 10]Expected:
Model(inputs=..., outputs=Dense(...))Test Case 2
Input:
[VGG16(weights='imagenet', include_top=False, input_shape=(224, 224, 3)), 20]Expected:
Model(inputs=..., outputs=Dense(...))+ 3 hidden test cases