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Materials for deep NLP course
Jupyter Notebook Python
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seminar_01 updated fork Nov 9, 2018
seminar_02 updated fork Nov 9, 2018


ATTENTION: Please, do not share your task solutions on GitHub or anywhere else!

Also, please do not add your name to your homework, since we try to keep review process anonymous.

Seminars plan:

  1. Intro to NLP, intro to word embeddings
  2. Word embeddings: Word2Vec, GloVe, fastText
  3. Language modeling, softmax crossentropy loss, one layer neural networks
  4. Neural networks and backpropagation, optimization
  5. Practical tips, gradient checking, overfitting, regularization, activation functions
  6. Reccurent neural networks
  7. GRU and LSTM, intro to machine translation
  8. CNN for text classification
  9. Machine translation, attention mechanism
  10. Dynamic memory networks, Deep Contextualized Word Representations, future of NLP
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