Natural Language Processing

Catalog description

Explores foundational concepts in Natural Language Processing (NLP) with a focus on artificial intelligence applications. Investigates core NLP tasks like text preprocessing, tokenization, and sentiment analysis, emphasizing real-world problem-solving. Utilizes libraries such as NLTK, SpaCy, and Hugging Face Transformers for text processing and language modeling. Engages in practical Python coding exercises, applying NLP techniques to real-world data and building models for tasks like machine translation, text classification, and named entity recognition. Prerequisite(s): AI 330 or CS 471 .