Hello world, welcome back to my page! Here I wanna show you another project that I just done, A Deep Autoencoder. So autoencoder is essentially just a kind of neural network architecture, yet this one is more special thanks to its ability to generate new data based on given sample represented in lower dimension. Here I am going to be using MNIST Handwritten Digit dataset in which each of its image samples has the size of 28 by 28 pixels. This size is then going to be flattened, hence we will have 784 values to represent each of those images.

As usual, I also include all code required for this project in the end of this article.

#neural-networks #computer-vision #autoencoder #deep-learning #ai