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 resorting back to V2 model but tweaking filters 32, 64 & 128, dropout 0.4, remove regularizers L1, L2 & none but keep batchnormalization 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 resorting back to V2 model but tweaking filters 32, 64 & 128, dropout 0.4, remove regularizers L1, L2 & none but keep batchnormalization to achieve the best performance, so that the model can accurately classify cherry leaves as healthy or containing powdery mildew.