- This quarter (2020-21 Winter), CS236G meets for in-class lecture T/Th 2:30 PM - 3:20 PM, Zoom.
- All class communication happens on the CS236G Piazza forum. For private matters, please make a private note visible only to the course instructors. For longer discussions with TAs and to get help in person, we strongly encourage you to come to office hours. If you need to contact us via email, please email individual TAs.
- The course content and deadlines for all assignments are listed in our syllabus.
- For general inquiries, please contact email@example.com.
Additional Project Mentors
- Learn and build generative adversarial networks (GANs), from their simplest form to state-of-the-art models.
- Implement, debug, and train GANs as part of a novel and substantial course project.
- Gaining familiarity with the latest cutting-edge literature on GANs.
- Reward risk-taking and creative exploration.
- In class lectures - twice a week on T/Th 2:30 PM - 3:20 PM (hosted on Zoom).
- Video lectures, programming assignments, and quizzes on Coursera
- The final project
|01/28/2021||3||Medicine + GANs||Video||Sharon’s Research Group|
|01/30/2021||3||Project Inspo||Sharon Zhou|
|02/05/2021||4||Finding Project Partners||Sharon Zhou|
|02/07/2021||4||How to Read a Paper||Slides
|02/11/2021||5||PyTorch for GANs Part 1||Notebook
|02/18/2021||6||PyTorch for GANs Part 2||Notebook
GAN Starter Notebook
|02/23/2021||7||Speech + GANs||Vincent Liu|
|02/25/2021||7||Differential Privacy||Tim Gianitsos|
|03/04/2021||8||Interim Project Showcase||Sharon Zhou|
|03/09/2021||9||Video + GANs||Sharon Zhou|
|03/11/2021||9||Text + GANs||Sharon Zhou|
|03/16/2021||10||Project Showcase||Sharon Zhou|
|03/18/2021||10||Project Showcase||Sharon Zhou|
Students are expected to have the following background:
- Familiarity with basic programming (CS106B or CS101)
- Familiarity with basics of deep learning (CS230 or CS221)
- Familiarity with the probability theory (CS 109 or STATS 116)
- Familiarity with linear algebra (MATH 51)
- 60%: Class project - creativity and equal participation within a group will be rewarded
- 35%: Programming assignments
- 5%: Midterm
- 0%: Attendance
- Extra credit: Your (or your GAN-generated) Memes. Requirements: Relevant and Appropriate with capital R and A there.
All students who are looking to audit the course should complete and submit the following form. You should receive an invitation to the course’s Canvas and the Coursera course in your Stanford email within 24-48 hours of submitting this form. Make a private piazza post (preferred) or email firstname.lastname@example.org if you did receive get the invitations.
This site was forked from CS230: Deep Learning (https://CS230.stanford.edu).