# Transfer Learning

On this chapter we will learn about 2 scenarios on transfer learning

* Initialize the network with a set of weights trained from another session. (Instead of initializing the network with random values).
* Load some network, freeze it's weights up to a certain point and re-train the rest, normally on a smaller dataset.

## References

* <https://discuss.pytorch.org/t/discussion-about-datasets-and-dataloaders/296>
* <http://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html>
* <https://medium.com/towards-data-science/transfer-learning-using-pytorch-4c3475f4495>
* <https://medium.com/towards-data-science/transfer-learning-using-pytorch-part-2-9c5b18e15551>
* <http://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html>