Approaching Almost Nlp Save

Approaching (Almost) Any Natural Language Processing Problem

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Approaching (Almost) Any Natural Language Processing Problem


  • The obvious intro to NLP
  • Bag of words
  • Hashing
  • Cleaning text data (stemming, lemmatization)
  • Tokenization of text data (from space-based to BPE and SentencePiece)
  • Word embeddings
  • Revisit LSTM, GRU, 1-D CNN, 2-D CNN
  • Decomposition-SVD
  • SVM, Logistic regression based models
  • Topic modelling
  • POS tagging, NER, entity detection/extraction using traditional approaches
  • Attention is all you need
  • Transformers
  • BERT, RoBERTa, XLM, and other transformer based models
  • Distillation of transformer based models
  • Entity extraction using transformer based models
  • Text summarization
  • Various assignments and projects

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