ACS 4520 Natural Language Processing (DS 2.5)
This course introduces methods of Natural Language Processing (NLP), and their applications to sequential data. Key topics covered include RNNs, Sequence models, and Language Models, and advanced concepts such as Attention and the BERT architecture. Students will learn to apply language models to a variety of tasks across NLP, such as Sentiment analysis, Neural Machine Translation, Question Answering and Text Summarization. Students complete individual projects in one of the topic areas and present their findings to the class. Prerequisites:
ACS 3510 (DS 2.1), ACS 3521 (DS 2.2)