UnsupervisedPretraining.md (654B)
1 # Unsupervised Pretraining 2 3 ML P576 4 5 **Definition:** Unsupervised pretraining is the process of pretraining a model on unlabeled data and then adding layers on top of the model using labelled data to get predictions. 6 7 This is often used because unlabeled data is often abundant, but labeled data is expensive. 8 9 We can do this with GANs as well as [Autoencoder](Autoencoder.md) With autoencoders we train the autoencoder to compress the data and then reuse the lower layers of this autoencoder as the lower layers for a neural network. This is useful because autoencoders are good at finding representations of the data without the need for labeled data.