spaCy: A Python Library for Natural Language Processing

This workshop will introduce participants to the spaCy Python library. spaCy provides components for named entity recognition, part-of-speech tagging, dependency parsing, sentence segmentation, text classification, lemmatization, morphological analysis, entity linking and more. The software provides support for more than 70 languages and it makes it easy to use pre-trained large language models and word vectors for both academic and industry problems.

Target audience: Students and researchers looking to learn a Python library for natural language processing.

Learning objectives: Participants will come away with the ability to use spaCy for a variety of natural language processing tasks.

Workshop format: Presentation and hands-on

Knowledge prerequisites: Some experience with Python is required.

Hardware/software prerequisites: Participants have two options: (1) Come with your own installation of Anaconda Python 3 distribution on your laptop. You can install spaCy. (2) Create an account on Adroit at least a few hours before the workshop (https://researchcomputing.princeton.edu/systems/adroit) and use the MyAdroit web interface for the workshop:
https://researchcomputing.princeton.edu/jupyter

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Co-hosted with: GradFUTURES

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