A beginner-friendly Jupyter notebook series introducing core Natural Language Processing concepts using Python.
NLP 101 demystifies natural language processing for beginners with no prior background in AI or linguistics. Each notebook builds on the previous, taking you from raw text to practical NLP applications.
| Notebook | Topic |
|---|---|
| 01 | Text basics — cleaning, tokenization, normalization |
| 02 | Stop words, stemming, and lemmatization |
| 03 | Bag of Words and TF-IDF |
| 04 | Sentiment analysis |
| 05 | Named Entity Recognition (NER) |
| 06 | Text classification |
| 07 | Introduction to word embeddings |
git clone https://github.com/aeleraqi/NLP101.git
cd NLP101
pip install -r requirements.txt
jupyter notebook- Python 3.8+
- NLTK, spaCy, scikit-learn, pandas
Author: Amr Eleraqi — Data Analyst | NLP Specialist | Machine Learning Expert | Educator
Affiliation: Toronto Metropolitan University, Ontario, Canada
