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Natural Language Processing
Applied and state-of-the-art topics in natural language processing. Language encoding, orthography, morphology, syntax, text processing, probabilistic language modeling, text classification, part-of-speech tagging, and lexical semantics, auto-complete, morphological analyses, named entity recognition, chatbots, smart search, sentiment analysis, and event discovery. Course Outline |
Syntax
TF-IDF
word2vec
Classical Sequence Modeling - RNN
Classical Sequence Modeling - LSTM
Neural Sequence Modeling – Transformers (BERT, etc.)
NLP libraries (e.g., PyTorch)
NLP Tasks (NER, WSD, event extraction, text classification, etc.)