do so autoencoders have been around for decades now people such as the laocoon and Hinton have used it are you all familiar with them I mean ok cool now let's move on to uses of auto-encoders right so the first being dimensionality reduction that means that you take your data you condense it into a lower dimensional space the reason for doing that is so that your data itself can be more easily represented visually and this will really assist before you applied into a neural network the next example would be denoising of data you can see that