-Brain Tumor detection model built using CNN and deployed with accuracy 93.02% .
-A python model built on google.colab.
-Data was installed from kaggle.com and it contained images of normal brain cts and brain with tumor cts
https://www.kaggle.com/datasets/navoneel/brain-mri-images-for-brain-tumor-detection
-The task was to classify these images using CNN.
-The accuracy was 93.02% .
-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.