The application of neural network methods---under the name "deep learning"---has led to breakthroughs in a wide range of fields, including in building language technologies (e.g. for search, translation, text input prediction). This course will provide a hands-on introduction to the use of deep learning methods for processing natural language. Methods to be covered include static word embeddings, feed-forward networks for text, recurrent neural networks, transformers, pre-training and transfer learning, with applications including sentiment analysis, translation, and generation.
| Days | Time | Location |
|---|---|---|
| Monday and Wednesday | 1:00 - 2:20 PM |
ARC G070
https://washington.zoom.us/j/98228669635 |
Note: while lectures will be delivered live at the above time and location, they will also be recorded and posted to the course Canvas page.
| Role | Name | Office | Office Hours |
|---|---|---|---|
| Instructor | Shane Steinert-Threlkeld |
GUG 415K and
https://washington.zoom.us/my/shanest |
Wednesday 3-5PM |
| Teaching Assistant | Saiya Karamali |
GUG 407 and
https://washington.zoom.us/s/92010041700 |
Tuesday 3:30 - 5:30PM |
While relevant readings are posted in the schedule below, the following are very good general resources. Names that are used to refer to these works are included in parentheses.
N.B.: All homework grading will take place on the patas cluster using Condor, so your code must run there. I strongly encourage you to ensure you have an account set up by the time of the first course meeting.
Unless explicitly mentioned below, the shared policies of the LING 57x course series apply to this course. Please read those policies for more information.
We understand that you may face hard times as we navigate an ever-changing world due to the COVID-19 pandemic and many other world events. If you find yourself struggling with a difficult concept; stressed over politics or health; slowed by monopolistic internet providers; or annoyed at a classmate, please remember that they might feel similar. Maybe not in your very moment, but certainly recently or soon. Some of you may find the return to hybrid teaching conducive to your style of learning and personality. Others may find it stressful or difficult. These are all normal reactions. Please have compassion and empathy, and assume that everyone is doing their best.
If you find yourself having trouble learning in class, please do not hesitate to let me or Saiya Karamali know. Our goal is to make this class a bright spot in these unprecedented times, and to do whatever we can to promote a healthy learning environment for all.
All deadlines and meeting times for this class are in "Pacific Time". Now that we are in Daylight Savings Time, this is UTC-7.
As per the policy above, all communication outside of the classroom should take place on Canvas. You can expect responses from teaching staff within 48 hours, but only during normal business hours, and excluding weekends.
N.B.: while CLMS students have a private Slack channel, I strongly encourage questions concerning course content and assignments to be posted to the Canvas discussion board, for two reasons. (i) Teaching staff will not look at Slack, so misinformation can spread. (ii) Not every student in the course is in the CLMS program, but they deserve to be included in course discussions and likely have many of the same questions.
Washington state law requires that UW develop a policy for accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW’s policy, including more information about how to request an accommodation, is available at Religious Accommodations Policy (https://registrar.washington.edu/staffandfaculty/religious-accommodations-policy/). Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form (https://registrar.washington.edu/students/religious-accommodations-request/).
Your experience in this class is important to me. If you have already established accommodations with Disability Resources for Students (DRS), please communicate your approved accommodations to me at your earliest convenience so we can discuss your needs in this course.
If you have not yet established services through DRS, but have a temporary health condition or permanent disability that requires accommodations (conditions include but not limited to; mental health, attention-related, learning, vision, hearing, physical or health impacts), you are welcome to contact DRS at 206-543-8924 or uwdrs@uw.edu or disability.uw.edu. DRS offers resources and coordinates reasonable accommodations for students with disabilities and/or temporary health conditions. Reasonable accommodations are established through an interactive process between you, your instructor(s) and DRS. It is the policy and practice of the University of Washington to create inclusive and accessible learning environments consistent with federal and state law.
Call SafeCampus at 206-685-7233 anytime – no matter where you work or study – to anonymously discuss safety and well-being concerns for yourself or others. SafeCampus’s team of caring professionals will provide individualized support, while discussing short- and long-term solutions and connecting you with additional resources when requested.