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Code examples, assignments and solutions for the course CS 20SI: TensorFlow for Deep Learning Research (winter 2017).

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CS 20SI: TensorFlow for Deep Learning Research

Code examples, assignments and solutions for the course CS 20SI: TensorFlow for Deep Learning Research (winter 2017).

Detailed syllabus and lecture notes can be found at http://cs20si.stanford.edu

Models include:

  • Linear Regression with Chicago's Fire-Theft dataset
  • Logistic Regression with MNIST
  • Word2vec skip-gram model with NCE loss
  • Convnets with MNIST
  • Autoencoder (by Nishith Khandwala)
  • Deepdream (by Jon Shlens)
  • Character-level language modeling
  • Style Transfer
  • Chatbot using sequence to sequence with attention

Misc

  • Examples on how to use data readers, TFRecord
  • Embedding visualization with TensorBoard
  • Usage of summary ops
  • Exercises to be familiar with other special TensorFlow ops
  • Demonstration of the danger of lazy loading
  • Convolutional GRU (CRGU) (by Lukasz Kaiser)