© CSE 595 Teaching Team | Designed by Martin Ziqiao Ma with Notion.
Welcome to CSE 595: Intro to Natural Language Processing!
- This is an introductory NLP course.
- This is a reissue of the previous NLP course.
- The schedule is tentative and subject to change.
‼️ Announcements
<aside>
📢 Announcement: If you have disabilities or medical conditions that require some form of accommodations, please make an appointment with the instructor within the first week of classes!
</aside>
Teaching Team
Teaching Team
📅 Tentative Schedule
Assessments & Lectures
Untitled
📍 Course Prerequisites and Policies
- Internal Communication
- Canvas: For lecture video recordings, assignment submission, and grading;
- Piazza: For general communication, teaming, QA, and discussions.
- Prerequisites
- Knowledge and experience in linear algebra and machine learning;
- Proficiency in Python programming (using NumPy and PyTorch).
- Late Submission Policy
- You have up to 3 days after the due date to submit your assignments;
- For each day delayed, you will receive a penalty for the assignment;
- After that cut-off date, you will receive 0 points;
- If there is a special circumstance, please get in touch with the instructor/TAs directly.
- Academic Honesty
- All homework assignments submitted must be your own work!
- Review the College of Engineering’s Honor Code.
- Generative AI Policies
- You may use Co-Pilot, ChatGPT, etc for consultation, not for directly copying answers;
- You need to acknowledge the use of the tools, if any.
- Special Accommodations
- If you have disabilities or medical conditions that require some form of accommodation, please make an appointment with the instructor within the first week of classes.
💯 Coursework and Grading
- Learning Goals
- Learn the basic principles and theoretical issues underlying natural language processing;
- Learn techniques and tools used to develop practical, robust systems;
- Gain insight into many open research problems in natural language.
- Individual Assignments (15% $\times$ 4 = 60%)
- Programming portion: starter code provided;
- Written portion: use $\LaTeX$;
- Submission through Canvas.