DEEP Learning
Class overview
This course covers the fundamentals of deep neural networks at the undergraduate level. We introduce linear regression, multi-layer perceptrons, back-propagation, and automatic differentiation. We will also discuss Convolutional Neural Networks, Recurrent Neural Networks, and Transformers. The course will be a combination of lectures, presentations, and machine learning competitions.
Lecturer: Qi (Rose) Yu (roseyu@ucsd.edu)
TA:
Sophia Sun (shs066@ucsd.edu)
Lakshya LNU (llnu@ucsd.edu)
Andrew Ghafari (aghafari@ucsd.edu)
Arnav Parekhji (aparekhji@ucsd.edu)
Tutor:
James Zhao (jjz005@ucsd.edu)
Yash Shah (ynshah@ucsd.edu)
Yunchao Yao (y8yao@ucsd.edu)
Brooks Niu (rniu@ucsd.edu)
Lecture: 2:00 pm - 3:20 pm PT, Tuesday, Thursday PETER 110
Discussion: 2:00 pm - 2:50 pm PT, Friday, MOS 0114
Office Hour:
Rose Yu | 5:00 pm - 6:00 pm | Monday | EBU3B 3208
Sophia Sun | 11:00am - 12:00 pm | Friday | EBU3B B250A
Lakshya LNU | 11:15am - 12:15 pm | Tuesday | EBU3B B250A
Andrew Ghafari | 12:00pm - 1:00 pm | Thursday| EBU3B B250A
Arnav Parekhji | 9:30am - 10:30am | Wednesday | Zoom: https://ucsd.zoom.us/j/7154489061
James Zhao | 11:00am - 12:00 pm | Wednesday | EBU3B B250A
Yash Shah | 5:00 pm - 6:00 pm | Thursday | EBU3B B240A
Yunchao Yao | 11:00 am - 12:00 pm | Thursday | EBU3B B240A
Brooks Niu | 1:00 pm - 2:00 pm | Wednesday | Zoom: https://ucsd.zoom.us/j/93542387707
Daniel George |12:00pm - 1pm |Friday | Zoom: https://ucsd.zoom.us/j/7973551377
Syllabus
Week 1 (April 3rd) Introduction and Background HW 1 release
Week 2 (Apr 10th) Multi-layer perceptron
Week 3 (Apr 17th) Automatic Differentiation HW 2 release
Week 4 (Apr 24th) Convolutional neural network
Week 5 (May 1st) Recurrent neural network HW3 release
Week 6 (May 8th) Mid-term week
Week 7 (May 15th) Deep learning implementation HW4 release
Week 8 (May 22nd) Attention and Transformer Milestone report due
Week 9 (May 29th) Graph neural network
Week 10 (June 5 th) Presentation week Final report due
Lectures
Class Assessment
40 % homework (10% x 4)
35 % Kaggle competition
5 % milestone report
10 % final report
10 % final presentation
10 % competition ranking
25 % Mid-term exam
Resources
Reading Materials
FAQ
Q: What are the pre-requisites?
(MATH 31BH or MATH 20C) and (ECON 120A or ECE 109 or CSE 103 or MATH 181A or MATH 183, MATH 170A);
Proficiency in Python.
Q: Can first year undergraduates take this course?
Restricted to students with sophomore, junior, or senior standing within the CS25, CS26, CS27, CS28, EC26, and DS25 majors.
All other students will be allowed as space permits.
About me
My Chinese name is Qi Yu. That is also the instructor's name in the registrar's office. I publish under the name Rose Yu. You can learn more about my research at my personal website.