Prerequisites: ((COMP 400B or COMP 271) and (MATH 131 OR equivalent) and (STAT 103 OR equivalent)) OR instructor permission.
In this course, students examine in depth the problems, methods, and applications of NLP. Topics will include information retrieval, sentiment analysis, machine translation, document classification, and question answering. We will also cover the underlying theory from probability, statistics, and machine learning that are crucial for the field.
Outcomes: Students will explain areas of NLP such as information retrieval, sentiment analysis, machine translation, document classification, question answering; Students will apply tools of NLP to a domain of their choice.
In this course, students examine in depth the problems, methods, and applications of NLP. Topics will include information retrieval, sentiment analysis, machine translation, document classification, and question answering. We will also cover the underlying theory from probability, statistics, and machine learning that are crucial for the field.
Outcomes: Students will explain areas of NLP such as information retrieval, sentiment analysis, machine translation, document classification, question answering; Students will apply tools of NLP to a domain of their choice.