Welcome to the first week of the TAP Institute's 2023 spaCy course. This course aims to introduce complete beginners to spaCy, a powerful open-source library for Natural Language Processing in Python. By the end of this week, you will have a solid foundation of the basics of spaCy, preparing you for more advanced topics in Week 2 (rules-based spaCy) and Week 3 (machine learning with spaCy).
This repository contains the notebooks for each day of the course, stored in the 'notebooks' directory. Each notebook provides step-by-step guidance for that day's topic. There are three notebooks for this week:
- Day 1
- Day 2
- Day 3
The course material is supplemented with relevant data and images which are stored in the 'data' and 'images' directories respectively.
spaCy is a free, open-source library for advanced Natural Language Processing (NLP) in Python. It's designed specifically for production use and helps you build applications that process and "understand" large volumes of text. It can be used to build information extraction or natural language understanding systems, or to pre-process text for deep learning.
You'll need to have spaCy v3.5.0 installed for this course. You can install spaCy using pip:
pip install -U spacy==3.5.0This repository has the following structure:
notebooks/- Contains the Jupyter notebooks for each day of the course.data/- Contains datasets used in the notebooks.images/- Contains images used in the notebooks.
- Day 1: Introduction to spaCy and basics of Natural Language Processing (NLP)
- Day 2: Deep dive into spaCy's features and capabilities
- Day 3: Practical exercises to reinforce your understanding of spaCy
Feel free to clone this repository and explore the material at your own pace.
git clone https://github.com/wjbmattingly/tap-2023-spacy-01Join us on this exciting journey to unlock the power of text data with spaCy!
This project is licensed under the terms of the MIT license.