This course will introduce students to the methods and tools used for developing Natural Language Processing and Machine Learning software. Students will work as a team to develop a machine learning system that can compete in a range range of increasingly challenging problems in natural language semantics. Teams will choose which challenge to tackle from a collection of tasks for computational semantic analysis. Students will have an opportunity to compare their systems against teams from other institutions and present their results. Participation requires permission of the instructor
This course can also serve as the basis for a "Senior Thesis or Project"
Credits: 3
Enrollment Cap: 5 students
Prerequisites: COMS W 4705 (Natural Language Processing) or COMS W 4771 (Machine Learning) or extensive software experience
Adam Poliak
Email: apoliak@barnard.edu
Office hours: TBA
Zoom link:
The course contains the following components:
By the end of this course, students will:
Goldberg, Yoav. "Neural network methods for natural language processing." Synthesis Lectures on Human Language Technologies 10.1 (2017): 1-309.
All additional course readings will be made available on Canvas.
The schedule will be broken into the following:
Course meetings will be determined based on availability and times that work best for the students. This will be determined during the first week. During course meetings, students will report their progress for the week and one student will provide a summary of the week's reading.
Students will have the option of using their system to compete in The 15th International Workshop on Semantic Evaluation (SemEval) between January 10th through January 31st. This is not required and the students' grade will not be dependent on participating in the competition. Students who elect to compete in the competition will have the opportunity to present their work at the SemEval workshop in Summer 2021.
The course will culminate in a write-up of the project following this format.
| Grade Criteria | Grade Scale | ||
|---|---|---|---|
| Percent | Letter Grade | Percent | |
| Participation | 15% | A+ | 97 - |
| Summaries for Readings | 20% | A | 93 - 96 |
| Presentations | 20% | A- | 90 - 92 |
| Midsemester write up | 15% | B+ | 87 - 89 |
| Final write up | 30% | B | 83 - 86 |
| B- | 80 - 82 | ||
| C+ | 77 - 79 | ||
| C | 73 - 76 | ||
| C- | 70 - 72 | ||
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