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A python model built on google.colab, where data was installed from kaggle.com and it contained images of corona virus, pneumonia (lung disease) and normal images , the task was to classify these images and I used CNN, the accuracy was 95.45% .

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Sarah-Hesham-2022/Covid19_Pneumonia_Normal_Image_CNN_Classification-and-Deployment

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Covid19_Pneumonia_Normal_Image_CNN_Classification

-Covid19_Pneumonia and Normal CNN classification python model of accuracy 92% .

-A python model built on google.colab.

-Where data was installed from kaggle.com and it contained images of corona virus, pneumonia (lung disease) and normal images .

https://www.kaggle.com/datasets/pranavraikokte/covid19-image-dataset

-The task was to classify these images with CNN.

-The accuracy was 92% .

-While running this model on google colab, you have to be signed in to kaggle.com and make a token and upload it, as I am connecting kaggle with colab so as not to download the data on my PC.

-Also at the end I am saving the model.h5 on google drive, so there will be a connection request to your google drive account to save the model.

-At the end I have made a python code to use my .h5 file, i.e. deep learning model to test new data randomly selected from the internet.

-Simple Model Deployment.

-I have also uploaded the random pictures from google search to test the model.

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A python model built on google.colab, where data was installed from kaggle.com and it contained images of corona virus, pneumonia (lung disease) and normal images , the task was to classify these images and I used CNN, the accuracy was 95.45% .

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