S.no. | Topics Covered | Notebook |
---|---|---|
1. | Basics, tokenization, n-gram creation, stopwords removal, stemming, lemmatizing, feature-vector creation | Lab 1.0 |
2. | Introduction to the Indic NLP Library by @anoopkunchukuttan , text normalization, sentence splitting, tokenization, detokenization, script conversion, Romanization, Indicization, word segmentation | Lab 1.1 |
3. | Creating a basic rule-based PoS tagger for English and Urdu | Lab 2.0 |
4. | CRF based NER Tagging for English | Lab 3.0 |
5. | Lesk-based Word Sense Disambiguation | Lab 4.0 |
6. | Continuing working with words as features, with focus on building language models | Lab 5.0 |
7. | Word Embeddings with word2vec and other methods | Lab 6.0 |
8. | Visualizing ELMo Contextual Vectors for Word Sense Disambiguation. | Lab 7.0 |
9. | Named Entity Recognition using Language Models: DistilBERT | Lab 8.0 |
10. | Named Entity Recognition using Language Models: XLM-R | Lab 8.1 |
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Programs written throughout the duration of the course on NLP.