As a data scientist I want to train the CNN model using the pre-processed dataset with re-sized images 75 x 75 and optimize the hyperparameters min value 128, max value 256, step 32, filters 32, 64 & 64, dropout 0.5, with values 1e-3, 1e-4 on a Relu activation and loss of binary_crossentropy to achieve the best performance, so that the model can accurately classify cherry leaves as healthy or containing powdery mildew.
As a data scientist I want to train the CNN model using the pre-processed dataset with re-sized images 75 x 75 and optimize the hyperparameters min value 128, max value 256, step 32, filters 32, 64 & 64, dropout 0.5, with values 1e-3, 1e-4 on a Relu activation and loss of binary_crossentropy to achieve the best performance, so that the model can accurately classify cherry leaves as healthy or containing powdery mildew.