Курс по автоматической обработке текстов.
email: [email protected]
telegram: @king_menin
1 (21 ) | : . , . Sequence labeling | , , POS-, . | . . |
2 (28 ) | . . | ||
3 (12 ) | . | . | . |
4 (26 ) | . | . | . |
: [git:sem1](https://github.com/king-menin/nlp-course/tree/master/sem%201)
1: intro.pdf
2: morphology.pdf, sem1.ipynb, : hw1.ipynb
Python:
import nltk
nltk.download('stopwords')
nltk.download('punkt')
: [git:sem2](https://github.com/king-menin/nlp-course/tree/master/sem%202)
3: topic modeling.pdf, topic modeling.ipynb ( , ) topic modeling.ipynb
4: classification.pdf, classification.ipynb ( , ) classification.ipynb, data-train.txt, : hw2.ipynb
Python:
import nltk
nltk.download('stopwords')
nltk.download('punkt')
: [ru.vec](https://www.dropbox.com/s/0x7oxso6x93efzj/ru.tar.gz), [all.txt](https://www.dropbox.com/s/ksm21a8y6lgl511/all.txt.zip?dl=0)
5: distributive semantic.pdf, ds.ipynb
Python:
: [ru.vec](https://www.dropbox.com/s/0x7oxso6x93efzj/ru.tar.gz), [dinos.txt](https://www.dropbox.com/s/e0v7ex10s5kfu0y/dinos.txt?dl=0), [articles_lemmatized_noSW.csv](https://www.dropbox.com/sh/513tgmhz2ollna5/AAB6W-J3zwKDxKHSUnhjaYINa?dl=0&preview=articles_lemmatized_noSW.csv)
6: neural networks on nlp.pdf, 4_RU_FNN_CNN.ipynb, 5_LM.ipynb
Python: