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Using GANs to improve generalization in a semi-supervised setting - trying it in open datasets


In many practical machine learning classification applications, the training data for one or all of the classes may be limited. We will examine how semi- supervised learning using Generative Adversarial Networks (GANs) can be used to improve generalization in these settings. The full approach from training to model deployment will be demonstrated, using AWS Lambda and/or AWS Sagemaker


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