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DFL is a compendium of curricula to help you deeply understand Machine Learning.
Each of our posts are a self-contained lesson plan targeting a significant research paper and complete with readings, questions, and answers.
We can guarantee that honestly engaging the material will leave you with a thorough understanding of the methods, background, and significance of that paper.
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InfoGAN is an extension of GANs that learns to represent unlabeled data as codes. Representation learning is an important aspect of unsupervised learning, and GANs are a flexible and powerful interpretation. This makes InfoGAN an important and interesting stepping stone in representation learning. ⟹
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