As a data scientist I want to train the CNN model using the pre-processed dataset with re-sizes images 100 x 100 and optimize the hyperparameters reverting back to V2 but tweaking activation of sigmoid to softmax instead and changing loss - binary_crosstentropy to sparse_categorical_crossentropy instead 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-sizes images 100 x 100 and optimize the hyperparameters reverting back to V2 but tweaking activation of sigmoid to softmax instead and changing loss - binary_crosstentropy to sparse_categorical_crossentropy instead to achieve the best performance, so that the model can accurately classify cherry leaves as healthy or containing powdery mildew.