[Syllabus] EECS 595: Natural Language Processing
EECS 595: Natural Language Processing, Fall 2020
Course Links and Information
Instructor: Joyce Chai (email@example.com)
Lecture Time: Wednesday 1:30-3:00 pm; Friday 3:00-4:30 pm
Lecture Location: see canvas
- Instructor: Wednesday, 3:00-4:00 pm, EST
- Paul: Monday and Friday, 2:00-3:00 pm, EST
- Shane: Tuesday, 10:30-11:30am, EST
The field of Natural Language Processing (NLP) is primarily concerned with computational models and computer algorithms to process human languages, for example, automatically interpret, generate, and learn natural language. In the past twenty years, the rise of the world wide web, mobile devices, and social media have created tremendous opportunities for exciting NLP applications. The advances in machine learning have also paved the way to tackle many NLP problems in the real world. This course provides an introduction to the state of the art in modern NLP technologies. In particular, the topics to be discussed include: syntax, semantics, discourse, and their applications in information extraction, machine translation, sentiment analysis, and dialogue systems.
Speech and Language Processing, an introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, third edition (draft), by Daniel Jurafsky and James Martin, Prentice Hall (JM for short).
Proficiency in Python programming. Some knowledge in machine learning is preferred but not required.
The work in this course consists of four homework assignments and a final project. Each assignment may include a written portion and a programming portion. All homeworks must be your own work.
- Homework assignments: 60%
- Final Project: 40%
Late submission policy
You have up to 7 days after the due date to submit your assignments. After that cut off date, you will receive 0 point. For each day delayed, you will receive 0.5 point penalty for the written assignment and 0.5 point penalty for the programming assignment. If there is a special circumstance, please contact the instructor/TAs directly.
Lectures and Discussions
Schedule of Topics and Assignments
Lecture and Discussion Videos
All homework assignments submitted must be your own work. Review the college of Engineering’s Honor Code here: http://www.engin.umich.edu/college/academics/bulletin/rules (Links to an external site.)
If you have disabilities or medical conditions which require some form of accommodations, please make an appointment with the instructor within the first week of classes.
Notes: The instructor reserves the right to modify course policies and the course calendar according to the progress and needs of the class.