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Fakultät für Informatik

Deep Learning

Contents:

  • Linear models for image classifications
  • Regularization methods (Dropout, Batch-Norm, )
  • (Stochastic) optimization methods (SGD, Momentum, AdaGrad, Adam)
  • Backpropagation
  • Convolutional neural networks
  • Recurrent neural networks
  • Generative models