Latin Natural Language Processing with Python and CLTK

Learn Latin Natural Language Processing through a comprehensive video series that explores computational analysis of Classical Latin texts using Python and the Classical Language Toolkit (CLTK). Master essential NLP techniques including corpus reading, data standardization and preparation, morphological analysis through declining and conjugating words, lemmatization, and macronization for proper vowel length marking. Develop skills in various tokenization methods including line, sentence, and word-level processing of Latin texts. Discover how to implement Named Entity Recognition specifically designed for Classical Latin materials and gain practical experience in packaging spaCy models with custom factories for digital humanities applications.

Syllabus

Introduction to NLP and CLTK (Latin NLP with Python - 01)
Installing CLTK (Latin NLP with Python 02)
CLTK Corpus Reader (Latin NLP with Python 03)
Data Standardization (Latin NLP with Python 04)
Data Preparation (Latin NLP with Python 05)
Declining and Conjugating Words (Latin NLP with Python 06)
CLTK Lemmatizer (Latin NLP with Python 07)
CLTK Macronizer (Latin NLP with Python 08)
CLTK Line Tokenization (Latin NLP with Python 09)
CLTK Sentence Tokenization (Latin NLP with Python 10)
CLTK Word Tokenization (Latin NLP with Python 11)
Classical Latin Named Entity Recognition (NER for DH 10.01)
How to Package spaCy Models (Even with Custom Factories) (NER for DH 11)