Natural Language Processing UWR 2020

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Assigments and syllabus from Natural Language Processing @ University of Wrocław 2020 Class

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Syllabus

1. Introduction to NLP
2. MaxMatch&ReverseMaxMatch
3. Byte Pair Encoding
4. WordPiece
5. N-Gram Models
6. N-Gram Text Generation
7. Smoothing for N-Gram Models
8. Class based N-Grams
9. Laplace Smoothing
10. Deleted Interpolation
11. Absolute Discounting
12. Kneser-Ney Smoothing
13. Katz back-of
14. ARPA
15. PERPLEXITY
16. N-Gram Text Reconstruction
17. N-Gram Classification
18. Collocations
19. Grammar in NLP (linguistics point of view)
20. Stemming and lemmatization
21. Vector Immersion
22. Word2Vec
23. Glove
24. HMMs in NLP
25. Viterbi Algorithm
26. EM for HMM
27. POS Tagging
28. DAN
29. RNN
30. Context-free grammars in NLP
31. TreeBanks
32. Parsing
33. CYK
34. Recursive Descent Parser
35. Shift-Reduce
36. Earley parser
37. Chart parser
38. Phrase structure grammars
39. Chunking
40. Named Entity Recognition
41. Probabilistic context-free grammars
42. Statistical parsing
43. Dependency grammars