using deep learning to classify x-ray image

steps:

1. Import Libraries
2. EDA
3. create dataset
4. images preprocess and use class weight to solve imbalance problem
5. Training the Model
6. Compute Accuracy
7. Making Predictions
8. Conclusion

we try several model :

1. first model: simple deep learning model :: Accuracy: 0.78 - Recall: 0.72 - F1 Score: 0.73
2. second model we did some fine tuning by adding drop out layer: ::Accuracy: 0.73 - Recall: 0.64 - F1 Score: 0.64
3. third model anther fine tuning by adding dense layer: ::Accuracy: 0.74 - Recall: 0.66 - F1 Score: 0.65
4. anther pretrained model vgg19 ::Accuracy: 0.78 - Recall: 0.70 -F1 Score: 0.72
5. then we try pretrained model vgg16 ::Accuracy: 0.79 - Recall: 0.72 - F1 Score: 0.73

the highest accuracy and f1score is vgg16 so we use this model in reference