# 【共筆】Clustering And Dimensionality Reduction - Deep Dive》時程總表

**URL:** https://vip.studycamp.tw/t/%E3%80%90%E5%85%B1%E7%AD%86%E3%80%91clustering-and-dimensionality-reduction-deep-dive%E3%80%8B%E6%99%82%E7%A8%8B%E7%B8%BD%E8%A1%A8/7288
**Category:** 機器學習
**Created:** [2024年六月8日 14:42 UTC](https://vip.studycamp.tw/t/%E3%80%90%E5%85%B1%E7%AD%86%E3%80%91clustering-and-dimensionality-reduction-deep-dive%E3%80%8B%E6%99%82%E7%A8%8B%E7%B8%BD%E8%A1%A8/7288 "2024-06-08T14:42:20Z")
**Posts on this page:** 1
**Page:** 1

<div class="post-metadata">

### Author: ![WIKI](https://vip.studycamp.tw/user_avatar/vip.studycamp.tw/wiki/32/6678_2.png) [@WIKI](https://vip.studycamp.tw/u/WIKI)
#### Post date: [2024年六月8日 14:42 UTC](https://vip.studycamp.tw/t/%E3%80%90%E5%85%B1%E7%AD%86%E3%80%91clustering-and-dimensionality-reduction-deep-dive%E3%80%8B%E6%99%82%E7%A8%8B%E7%B8%BD%E8%A1%A8/7288/1 "2024-06-08T14:42:20Z")

</div>

> **如何提高完課率： [我對共同學習的一些想法](https://vip.studycamp.tw/t/topic/3649/1)**

## ▌共學說明

## [**Zoom meeting 連結**](https://us06web.zoom.us/j/83799836736?pwd=0mtR9IYrDaIQAXCGXysTZ7WCxZnthB.1)

7月20日開始，每週六晚上10點線上分享及討論（需登入 zoom）。

**共學進行方式** ：每週由參與夥伴各自上課，輪值分享。

**本文設為共筆，歡迎大家共同維護更新。** （為方便點擊網址進入主文，本文已關閉回文功能）

* * *

## ▌課程進度安排

> **參考文章：[使用 ChatGPT 協助修改進度表格](https://vip.studycamp.tw/t/topic/7029/1)**

| 日期 | 主題 | 導讀 | 筆記 | 錄影 |
| --- | --- | --- | --- | --- |
| 7月20日 | Python data science libraries (27-40) | Ted | [筆記](https://hackmd.io/@YukTed/rJRZ3ktOA) | [YouTube](https://www.youtube.com/watch?v=kY0r4MKAdLE&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=1) |
| 7月27日 | Python data science libraries (41-54) | Ted | [筆記](https://hackmd.io/@YukTed/BJj1Q8KuC) | [YouTube](https://www.youtube.com/watch?v=RT-_CdhMrS8&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=2) |
| 8月3日 | K-means clustering - part 1 (55-63) | fy | [筆記] | [YouTube](https://www.youtube.com/watch?v=ezt6uQrKiWw&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=3) |
| 8月10日 | K-means clustering - part 1 (64-68) | fy | [筆記] | [YouTube](https://www.youtube.com/watch?v=2ayEs04gjrc&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=4) |
| 8月17日 | Principal component analysis (PCA) (69-78) | spencer | [筆記](https://github.com/spencer18001/Clustering-And-Dimensionality-Reduction---Deep-Dive/blob/main/05/05_note.ipynb) | [YouTube](https://www.youtube.com/watch?v=WwQXMt1RuH0&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=5) |
| 8月24日 | Principal component analysis (PCA) (79-86) | spencer | [筆記](https://github.com/spencer18001/Clustering-And-Dimensionality-Reduction---Deep-Dive/blob/main/05/05_note_part2.ipynb) | [YouTube](https://www.youtube.com/watch?v=lYkHFq--A_4&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=6) |
| 8月31日 | Uniform Manifold Approximation and Projection for Dimension Reduction (UMAP) (87-92) | Howard | [筆記](https://app.heptabase.com/w/516287c04c6a50ea432d570370b57ccdebe790680133fb426fa37baf5d1b1ab2) | [YouTube](https://www.youtube.com/watch?v=qswIGeFh56o&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=7) |
| 9月7日 | Uniform Manifold Approximation and Projection for Dimension Reduction (UMAP) (93-97) | Howard | [筆記](https://app.heptabase.com/w/516287c04c6a50ea432d570370b57ccdebe790680133fb426fa37baf5d1b1ab2) | [YouTube](https://www.youtube.com/watch?v=92yWnMpPHys&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=8) |
| 9月14日 | Uniform Manifold Approximation and Projection for Dimension Reduction (UMAP) (98-104) | Howard | [筆記](https://app.heptabase.com/w/516287c04c6a50ea432d570370b57ccdebe790680133fb426fa37baf5d1b1ab2) | [YouTube](https://www.youtube.com/watch?v=pzHSsc9PJ_0&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=9) |
| 9月21日 | K-means clustering - part 2 (105-118) | fy | [筆記](https://yielding-perigee-ff9.notion.site/595d8de8bb77481b8a967c6985333c61?v=6cac0b9a12e5489297c0fd72b9f6abd1&pvs=4) | [YouTube](https://www.youtube.com/watch?v=Y6kThfY742M&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=10) |
| 9月28日 | K-means clustering - part 2 (119-126) | fy | [筆記](https://yielding-perigee-ff9.notion.site/595d8de8bb77481b8a967c6985333c61?v=6cac0b9a12e5489297c0fd72b9f6abd1&pvs=4) | [YouTube](https://www.youtube.com/watch?v=hvBlvmo8lfo&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=11) |
| 10月5日 | Case study - clustering cells based on RNA data | syd | [筆記] | [YouTube](https://www.youtube.com/watch?v=TNc7oV3-a6w&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=12) |
| 10月12日 | Agglomerative hierarchical clustering (136-143) | Ted | [筆記](https://hackmd.io/@YukTed/Hy1r28vkJe) | [YouTube](https://www.youtube.com/watch?v=qZewscS26GE&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=13) |
| 10月19日 | Agglomerative hierarchical clustering (144-150) | Ted | [筆記](https://hackmd.io/@YukTed/B1gXvlYJkg) | [YouTube](https://www.youtube.com/watch?v=M0jP9iQLM48&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=14) |
| 10月26日 | Density based clustering (151-159) | spencer | [筆記](https://github.com/spencer18001/Clustering-And-Dimensionality-Reduction---Deep-Dive/blob/main/10/10_note.ipynb) | [YouTube](https://www.youtube.com/watch?v=cVGNSu4X-LQ&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=15) |
| 11月2日 | Density based clustering (160-169) | spencer | [筆記](https://github.com/spencer18001/Clustering-And-Dimensionality-Reduction---Deep-Dive/blob/main/10/10_note_part2.ipynb) | [YouTube](https://www.youtube.com/watch?v=TVf5QHxVaO8&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=16) |
| 11月9日 | Density based clustering (170-179) | spencer | [筆記](https://github.com/spencer18001/Clustering-And-Dimensionality-Reduction---Deep-Dive/blob/main/10/10_note_part3.ipynb) | [YouTube](https://www.youtube.com/watch?v=kCTO8TUhH6s&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=17) |
| 11月16日 | Graph based clustering (180-188) | Howard | [筆記](https://app.heptabase.com/w/a0165636bbb9c2859798b8af7b8d86618bb5191ce522ee3c462984e30f2a6300) | [YouTube](https://www.youtube.com/watch?v=Ju_YAXsJ68U&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=18) |
| 11月23日 | Graph based clustering (189-199) | Howard | [筆記](https://app.heptabase.com/w/a0165636bbb9c2859798b8af7b8d86618bb5191ce522ee3c462984e30f2a6300) | [YouTube](https://www.youtube.com/watch?v=LU4gG2QJqQw&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=19) |
| 11月30日 | Wrap-Up | syd | [筆記] | [YouTube](https://www.youtube.com/watch?v=Ls9cV59mnTA&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=20) |

## ▌延伸學習

| 日期 | 主題 | 導讀 | 筆記 | 錄影 |
| --- | --- | --- | --- | --- |
| 12月14日 | 論文閱讀：DenMune: Density peak based clustering using mutual nearest neighbors | | [筆記] | [YouTube](https://www.youtube.com/watch?v=qqV04Up2jHM&list=PLxHlVV5gCbcO-B8HWlMQvS61fUUrJBYrZ&index=21) |
| 12月21日 | denmune: demo | | [筆記](https://colab.research.google.com/drive/1a1fNm9XAopwUw0NqHQOltFEsm9C1ihR7#scrollTo=Oc3weUActzu3) | [YouTube] |

> **[DenMune: Density peak based clustering using mutual nearest neighbors](https://arxiv.org/abs/2309.13420)**
>
> Many clustering algorithms fail when clusters are of arbitrary shapes, of varying densities, or the data classes are unbalanced and close to each other, even in two dimensions. A novel clustering algorithm, DenMune is presented to meet this...

> **[GitHub - scikit-learn-contrib/denmune-clustering-algorithm: DenMune a clustering algorithm that can find...](https://github.com/scikit-learn-contrib/denmune-clustering-algorithm)**
>
> DenMune a clustering algorithm that can find clusters of arbitrary size, shapes and densities in two-dimensions. Higher dimensions are first reduced to 2-D using the t-sne. The algorithm relies on a single parameter K (the number of nearest neighbors). The results show the superiority of DenMune. Enjoy the simplicty but the power of DenMune.

* * *

## ▌課程資訊

[**Clustering And Dimensionality Reduction - Deep Dive**](https://www.udemy.com/course/clustering-and-dimensionality-reduction-deep-dive/?couponCode=1DBF1DC916BB3D032CC5)  
類別：Development \> Data Science ║ 內容：27.5 hours ║ 原價：NT$1,290  
建立：2024-01-17 ║ 更新：2024-03-21 ║ 註冊：594人 ║ 語言：English ║ 字幕：有 ║ 評分：4.81 (45人)

* * *

## ▌共學守則

> [**Clustering And Dimensionality Reduction - Deep Dive 共學招募**](https://vip.studycamp.tw/t/topic/7050/1)

1. **會遲到 5分鐘以上或無法上線，先在 discord 知會其他人，勿常常缺席。**

2. **分享者需對自己當週分享的內容負責。**

3. **分享前或分享後，把筆記連結分享到論壇(不知道怎麼做可把連結貼在 discord，由班代代勞)。**

4. **課程中遇到問題，善用 Q&A 向老師提問，不要把問題留著。**

5. **積極提問、討論。**

* * *

## ▌大會報告：公開錄影

今年新募集課程，錄影皆公開上傳 YouTube，不同意者請不要參與共學，感謝配合。

**祝大家學習順利大成功！**