Use transfer learning for large image classification, going through these steps:

a$.$ Create a training set containing at least $100$ images per class. For example, you could classify your own pictures based on the location $($beach$,$ mountain, city, etc.$),$ or alternatively you can use an existing dataset $($e$.$g$.,$ from TensorFlow Datasets$).$

b$.$ Split it into a training set, a validation set, and a test set.

c$.$ Build the input pipeline, including the appropriate preprocessing operations, and optionally add data augmentation.

d$.$ Fine$-$tune a pretrained model on this dataset.