This project was developed as part of an introductory workshop for students with minimal Python experience. It offers a hands-on introduction to Natural Language Processing (NLP), with a focus on Named Entity Recognition (NER), sentiment analysis, and real-world data exploration.
Participants explore how to detect animals in text (even with typos), group them by species, analyze how people feel about those animals, and generate natural-language summaries based on real visitor reviews.
This workshop walks through a full NLP pipeline using visitor reviews from Edinburgh Zoo. Itβs designed to help beginners explore how we can use large language models to explore and extract information from written text, through the workshop.ipynb jupyter notebook.
Specifically, workshop.ipynb:
"pinguin" β "penguin")"penguins" β "penguin")"lion cub" β "lion")The notebook is structured to be beginner-friendly, with code and explanations provided step by step, and with a few prompts to guide the user to modify the code to explore the dataset themselves.
Clone the repo:
git clone https://github.com/nuriafari/NLP_workshop_zoo_reviews.git
cd NLP_workshop_zoo_reviews
Install dependencies
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python -m ipykernel install --user
Run the workshop Jupyter notebook:
jupyter notebook workshop.ipynb