Variational autoencoders and GANs have been 2 of the most interesting developments in deep learning and machine learning recently. Unsupervised learning means we’re not trying to map input data to targets, we’re just trying to learn the structure of that input data. You might be wondering, "how is this course different from the first unsupervised deep learning course?" In this first course, we still tried to learn the structure of data, but the reasons were different. In this new course, we want to learn the structure of data in order to produce more stuff that resembles the original data.

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