Summary

In this chapter we've had an extensive look at a new generation of deep learning models: autoencoders. We started with the Vanilla autoencoder, and then moved on to its variants: Sparse autoencoders, Denoising autoencoders, Stacked autoencoders, and Convolutional autoencoders. We used the autoencoders to reconstruct images, and we also demonstrated how they can be used to clean noise from an image. Finally, the chapter demonstrated how autoencoders can be used to generate sentence vectors. The autoencoders learned through unsupervised learning. In the next chapter we will delve deeper into some other unsupervised learning-based deep learning models.