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Generative models create data similiar to what they trained on Training these models is very hard One approach is using Generative Adversarial Networks (GANs) Facebook's Yann LeCun considers them "the most interesting idea in the last 10 years in ML" What are the differences between Discrimitive and Generative models? A discriminative model learns a function that maps the input data (x) to some desired output class label (y). In probabilistic terms, they directly learn the conditional distribution P(y x) A generative model tries to learn the joint probability of the input data and labels simultaneously, i.e. Facebook's Yann LeCun considers them "the most interesting idea in the last 10 years in ML" What are the differences between Discrimitive and Generative models? A discriminative model learns a function that maps the input data (x) to some desired output class label (y).