A repository dedicated to studying Natural Language Processing (NLP) using Python and common NLP libraries. It contains practical notebooks exploring fundamental text processing techniques and language modeling approaches.
Notebook demonstrating how to use spaCy for text processing and tokenization.
Topics covered:
- Basic text preprocessing
- Tokenization
- Linguistic features available in spaCy
- Practical NLP examples
Notebook exploring N-Gram language models using the NLTK library.
Topics covered:
- Text tokenization
- Building n-grams
- Language modeling basics
- Practical examples with NLTK
- Python
- Jupyter Notebook
- spaCy
- NLTK
This repository was created to practice fundamental NLP concepts, experiment with popular NLP libraries, and document the learning process through hands-on notebooks.
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