Bird species classification using Transfer learning - VGG16 & EfficientNetB0

Deep networks may perform poorly when dealing with the classification of relatively small image datasets because they need more data to train them. In such cases, one usually employs transfer learning, which uses deep learning models that are trained on enormous datasets such as ImageNet as feature extractors. The theory is that such deep networks have learned to extract meaningful features from an image using their layers, and they can be used in learning other tasks.