# 各項資料目錄

## 專案文件

|名稱|連結|簡述|
|-|-|-|
|Refined Proposal of GDSC|[link](https://hackmd.io/eC1DGkDlSZqh-VImbNKsDQ?view)|112下學期專案進行大綱|
|暑期workshop影片|[link](https://www.youtube.com/playlist?list=PLkB0SHqRKg-3fc--5gT0OAFpnT1bpHxco)|包含4個項目:regularization, SVM, 神經網路, Diffusion model|
|暑期workshop簡報&code|[link](https://drive.google.com/drive/folders/1ltt6Dl--FDB9Lh4lQ69jtuE3mEf8jpl5?usp=drive_link)||

## 學習資源

|名稱|連結|簡述|
|-|-|-|
|C229|[link](https://cs229.stanford.edu/)|stanford的課程|
|機器學習基石|[link](https://www.youtube.com/playlist?list=PLXVfgk9fNX2I7tB6oIINGBmW50rrmFTqf)|基礎~regularization|
|機器學習技法|[link](https://www.youtube.com/playlist?list=PLXVfgk9fNX2IQOYPmqjqWsNUFl2kpk1U2)|SVM~|
|SVD分解|[link](https://www.youtube.com/watch?v=OIe48iAqh8E)|把任意矩陣拆成三個矩陣，中間是對角矩陣的技術|
|Eigenvalue Decomposition|[link1](https://www.youtube.com/watch?v=KTKAp9Q3yWg), [link2](https://www.youtube.com/watch?v=DzqE7tj7eIM), [link3](https://www.youtube.com/watch?v=U8R54zOTVLw)||
|liner regression|[link1](https://chih-sheng-huang821.medium.com/線性回歸-linear-regression-3a271a7453e), [link2](https://www.youtube.com/watch?v=nk2CQITm_eo)||
|logistic regression|[link](https://www.youtube.com/watch?v=yIYKR4sgzI8), [link2](https://web.stanford.edu/~jurafsky/slp3/5.pdf)||

## 論文

|名稱|連結|先備知識|簡述|
|-|-|-|-|
|CVPR paper with code(ref)|[link](https://github.com/amusi/CVPR2024-Papers-with-Code/tree/master)|0|教你怎麼復現論文實驗，並提交code的開源項目|
|U-Net|[link](https://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/)|CNN、FCN|FCN的變體，可以用更少的資料做訓練，並有localization的功能|
|Attention is all-you-need (Transformer)|[link](https://proceedings.neurips.cc/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf)|||
|ResNet|[link](https://arxiv.org/abs/1512.03385)|||
|Diffusion Model|[link](https://arxiv.org/abs/2006.11239)|||
|GAN|[link](https://arxiv.org/abs/1406.2661)|||
|MobileNet|[link](https://arxiv.org/abs/1704.04861)|||

## 論文筆記、簡報

|名稱|連結|簡述|
|-|-|-|
|論文模板|[link](https://docs.google.com/presentation/d/1lrv1o-LnYbQz0g5OJB_mJIxwS_quef5hpiisQaX-s_E/edit#slide=id.g26b410a0b6a_0_140)|提供 by leader 許瑋哲|
|U-net共筆|[link](https://hackmd.io/@GDSC-lets-attack-machine-learning/S1WflS1Ca)||
|U-net簡報|[link](https://docs.google.com/presentation/d/1q_9rT920iSaEcAM_smHaGLRzehKKaRKvQKYseTMm9aM/edit?usp=sharing)|by 承志,侑哲|
|Transformer共筆|[link](https://hackmd.io/GhSOXL1vRzqzwKd7khf2ow)||
|Transformer簡報|[link](https://docs.google.com/presentation/d/1yDRqaF2o7k-sYzHIXrwnprAXkB32zRRf4Xy3KrC6GR8/edit?usp=sharing)|by 子萱,承志,侑哲|
|GAN共筆|[link](https://hackmd.io/@GDSC-lets-attack-machine-learning/BkEeh-d06)||
|GAN簡報|[link](https://docs.google.com/presentation/d/1NsAhaRysr5NT75AOp-jrjfx37bMu44IUX0Xd9HfMJnw/edit#slide=id.g2ceede511ef_0_75)|by 子萱,承志,侑哲|
|MobileNet共筆|[link](https://hackmd.io/@GDSC-lets-attack-machine-learning/BkVKElU-0)||
|MobileNet簡報|[link](https://docs.google.com/presentation/d/1OUU-TYKVIStKy79aMmR2LCpE6qTLt6MISgLNMvPrikw/edit?usp=sharing)|by 琍淩|
## 其他

|名稱|連結|簡述|
|-|-|-|
|YouZhe的理論知識筆記|[link](https://hackmd.io/@9UfXRWPzS62YaxdR7uwZ0Q/HJTzo_6bT)|我的一些理論知識的筆記，目前涵蓋regularization、SVM|