I recently wrote about, how to use a ‘imagenet’ pretrained efficientNet implementation from keras to create a SOTA image classifier on custom data, in this case the stanford car dataset. There are some details about BatchNormalization and how to start by training only the classifier layer and later train the complete network. But in the end it’s a good starter for beginners (using the jupyter notebook).

http://digital-thinking.de/keras-transfer-learning-for-image-classification-with-effificientnet/

If you are looking for a PyTorch example (not mine):

https://github.com/morganmcg1/stanford-cars