In the transfer learning example
https://www.tensorflow.org/tutorials/images/transfer_learning_with_hub
Is it possible to train on a certain number of flower images and save it for predictions and later load the saved model and train on a new set of flowers and be able to predict both the type of flowers
ie.
Train on flowers labels and data for [daisy, dandelion] save the model say model_d prediction works for daisy, dandelion
Load the saved model model_d Train on flowers labels and data for [roses, tulips] Would prediction work for [daisy, dandelion, roses , tulips]
ie do it in small batches but the model gains more labels over many training iterations
Any example on this would be helpful
