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In this tutorial, we will explore the realm of Variational Autoencoders (VAEs) using the renowned CelebA dataset. We will begin by training a VAE on this dataset and then explore tasks such as reconstructing the validation set, sampling from the standard normal distribution, probing the first 50 latent dimensions, and enhancing visual attributes through latent space arithmetic. We will also review the project directory structure and the CelebA dataset.
