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