DAVIAN Lab. Deep Learning Winter Study (2020)

Time: Monday 19:00 - 21:30

Date	Topic	Notes-by	Videos	Notes
4th January, 2021	(cs229) Lecture 2: Linear Regression and Gradient Descent	Junseok Ha	video	note
4th January, 2021	(cs229) Lecture 3: Weighted Least Squares. Logistic regression. Newton's Method	Minho Park	video	note
11th January, 2021	(cs229) Lecture 4: Perceptron. Exponential family. Generalized Linear Models	Minjung Kim	video	note
18th January, 2021	(cs231n) Lecture 2: Image Classification	Yeojeong Park	video	note
18th January, 2021	(cs231n) Lecture 3: Loss Functions and Optimization	Jaesung Lee	video	note
25th January, 2021	(cs231n) Lecture 4: Introduction to Neural Networks	Soonjoon Kwon	video	note
25th January, 2021	(cs231n) Lecture 5: Convolutional Neural Networks	Dongyeon Woo	video	note
1st February, 2021	(cs231n) Lecture 6: Training Neural Networks, part 1	Yuri Kim	video	note
1st February, 2021	(cs231n) Lecture 7: Training Neural Networks, part 2	Seungwoo Ryu	video	note
15th February, 2021	(cs231n) Lecture 9: CNN Architectures	Dongmin Yoo	video	note
15th February, 2021	(jchoo) Week10: Self-Supervised Learning (1) (2) (3) slide	Chan Lee	video	-
22th February, 2021	(cs231n) Lecture 10: Recurrent Neural Networks	Jaeyoon Chun	video	note
22th February, 2021	(lecun) Week 12: Deep Learning for NLP & Transformer	Dongyun Hwang	video	note
1st March, 2021	(cs231n) Lecture 13: Generative Models	Jaeun Jeong Haneol Lee	video	note