dl_tutorial

Course contents

  • Introduction to deep learning
  • Optimization methods
  • Regularization methods
  • Convolutional neural networks
  • Recurrent neural networks
  • Attention-based models
  • Graph neural networks
  • Deep learning with few labeled examples
  • Deep autoencoders
  • Flow-based and autoregressive generative models
  • Generative adversarial networks
  • Unsupervised learning via denoising