This repository provides materials for a workshop on Natural Language Processing (NLP) using Python. It is designed for students, researchers, developers, and hobbyists with basic Python knowledge, offering an introduction to NLP and text analytics without requiring prior NLP experience.

How It Works

The workshop utilizes Python libraries such as NLTK and scikit-learn, integrated within Jupyter notebooks. This approach allows for interactive exploration of NLP concepts, from basic text processing to more advanced techniques, facilitating a hands-on learning experience.

Quick Start & Requirements

• Install: Clone the repository, create and activate a Python virtual environment (virtualenv nlp-venv or conda create --name nlp-venv python=3.5), and install dependencies with pip install -r requirements.txt.
• Prerequisites: Python 3.4/3.5 (best-effort support for 2.7), NLTK data (punkt, stopwords, reuters), and Jupyter. NLTK data download is approximately 2GB.
• Run: Execute jupyter notebook to start the interactive environment.
• Docs: NLTK Data, Matplotlib FAQ

Highlighted Details

• Workshop materials have been presented at PyCon UK 2016, PyCon Ireland 2016, and PyCon Italy 2017.
• Includes instructions for resolving potential matplotlib backend issues on macOS.
• Data sources include Project Gutenberg and PyCon UK abstracts.

Maintenance & Community

• Main authors: Marco Bonzanini, Miguel Martinez-Alvarez.
• No explicit community links (Discord/Slack) or roadmap are provided in the README.

Licensing & Compatibility

• Code is under MIT license.
• Documentation and slides are under CC-BY license.
• Data is public domain or from specific GitHub repositories. Compatible with commercial use.

Limitations & Caveats

The project is tested with older Python versions (3.4-3.5) and may have best-effort support for Python 2.7, potentially leading to compatibility issues with modern Python environments.