https://www.coursera.org/learn/ai-deep-learning-capstone
1 . This Repository contains the 4 week AI Capstone project assignment using keras as a part of IBM-AI Engineering in which we need to classify a image containing a stone cracked or not by processing 40000 images in which nearly 30000 for training and 10000 for validation.
2 . 4th week is final assignment in which we need to campare performance in between pretrained models like Resnet50 and VGG16 using keras.
I ran both models to 2 epochs. Performance is as shown in below table.
| Model | Training Accuracy | Validation Accuracy | Test Accuracy | Valdation Loss | Training Loss |
|---|---|---|---|---|---|
| Resnet 50 | 91.08% | 93.88% | 54.19 | 0.0016 | 0.0070 |
| VGG16 | 99.76% | 99.81% | 98.0% | 7.4741e-05 | 0.0074 |
In the 2 models by the above data we can conclude VGG16 is appropriate for the above dataset. After all my final assignment is passed and graded 100%.
You can check it out here
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