In this lesson, we’ll delve into VAEs and their application to the MNIST dataset. Like traditional autoencoders, VAEs consist of an encoder and a decoder, but they go beyond simple image reconstruction. VAEs allow us to generate new data points by sampling from the learned latent space. Our focus will be on understanding the fascinating concept of generating new images from latent representations.

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