Transfer learning is a machine learning method where a model developed for a task is reused as the starting point for a model on a second task.
Since it is difficult to train a deep learning network from sratch, this is a wonderful technique to use pretrained networks as a starting point.

In this tutorial you will be going to use Inception V3 for retraining it on new classes, in simple words it can be thought as a feature extracter for your dataset.
This starts with loading pretrained model using TensorFlow save and restore, then you have to freeze the model add a layer for your outputs instead of 1000 classes you definitely want some different number of classes, and the last thing is to retrain the model for your bottleneck or the last layer of network.

Following blogs and repos are of utmost help while writing this tutorial.
https://codelabs.developers.google.com/codelabs/tensorflow-for-poets/#0
https://machinelearningmastery.com/transfer-learning-for-deep-learning/