STAT615_2024fall

Sharing the class-related online course and my written notes for this class, if you think this repository is helpful or you have any advise, please email me: zliu2276@wisc.edu/1148615059@qq.com. Thank you!

How to use this tutorial：

• Combine the online courses mentioned with Prof.Yan's course(https://yulingy.github.io/STAT615_Fall24.html), and choose the parts which you think you need to reinforce or learn.
• The number of（ * ) means the recommendation index, and (#) means this course is not as much helpful as the (*) courses for me.
• The Notes document includes my own handwritten notes and some notes/slides from the online courses, if authors mind I will delete those asap.
• I do not submit the materials of Professor Yan's Notes and Quizs, so if you have questions about the exams, just feel free to email me.

Bilibili online course:

SVM part: （***）

• https://www.bilibili.com/video/BV1Hs411w7ci?spm_id_from=333.788.videopod.episodes&vd_source=f93a900f93f134bf44c9945d7d2d9c22

LDA part:（***）

• https://www.bilibili.com/video/BV15W41127L2/?spm_id_from=333.999.0.0&vd_source=f93a900f93f134bf44c9945d7d2d9c22

Sub-Guassian and Inequality part:（***）

• https://www.bilibili.com/video/BV1xh411p7vF?spm_id_from=333.788.videopod.sections&vd_source=f93a900f93f134bf44c9945d7d2d9c22 【Section2.1-2.3】
• attached notebook is compiled by others, I sincerely show my thanks here.

Optimazation part（#）

(selection,if you need to learn the basic and full theory of Basic knowledge of convex problems, common methods of unconstrained optimization, constrained optimization theory and solving methods):

• https://www.bilibili.com/video/BV1m7411u72b/?spm_id_from=333.999.0.0&vd_source=f93a900f93f134bf44c9945d7d2d9c22

Non-parameter density estimation part:（#）

• Kernal estimation: https://www.bilibili.com/video/BV1ir4y1h7Pc/?vd_source=f93a900f93f134bf44c9945d7d2d9c22
• Histogram density estimation：https://www.bilibili.com/video/BV1Ei4y1c7eJ/?spm_id_from=333.337.search-card.all.click&vd_source=f93a900f93f134bf44c9945d7d2d9c22
• Notes of Prof.Yan: Your canvas files

Tree model/adaboost/Blending and Bagging part:（#）

• https://github.com/RedstoneWill/HsuanTienLin_MachineLearning (There are also videos in Bilibili)

LASSO and RIDGE Regression theory [basic] parts:（#）

• https://www.bilibili.com/video/BV1Bg4y1i76R?spm_id_from=333.788.videopod.episodes&vd_source=f93a900f93f134bf44c9945d7d2d9c22&p=3
• Because the author of this video has deleted slides before, email me if you need the slides of this courses plz.

SVD method:(***)

• https://zhuanlan.zhihu.com/p/29846048

LASSO with Proximal gradient method and Sub-gradient property:(***)(You can upload my notes to Chatgpt to get help)

• https://github.com/JustinDs0205/STAT615_2024fall

Hilbert space / Real number completeness part:(***)

• https://www.bilibili.com/video/BV1cV411T7hb/?spm_id_from=333.337.search-card.all.click&vd_source=f93a900f93f134bf44c9945d7d2d9c22

Kernel Method / PDS kernel definition and properties:（*）

• https://www.bilibili.com/video/BV1aE411o7qd?spm_id_from=333.788.videopod.episodes&vd_source=f93a900f93f134bf44c9945d7d2d9c22&p=37

The reproducing kernel Hilbert space parts:(**)

• https://www.bilibili.com/video/BV1ffYmeCEft?spm_id_from=333.788.videopod.sections&vd_source=f93a900f93f134bf44c9945d7d2d9c22
• https://www.bilibili.com/video/BV143execEQC?spm_id_from=333.788.player.switch&vd_source=f93a900f93f134bf44c9945d7d2d9c22

Mercer Theory part:(**)

• https://www.bilibili.com/video/BV1Fw4m1q7Ns/?spm_id_from=333.337.search-card.all.click&vd_source=f93a900f93f134bf44c9945d7d2d9c22

EM algorithm basis:(***)

• https://www.bilibili.com/video/BV1aE411o7qd?spm_id_from=333.788.videopod.episodes&vd_source=f93a900f93f134bf44c9945d7d2d9c22&p=60

Gaussian Mixture Model/GMM with EM:(***)

• https://www.bilibili.com/video/BV1aE411o7qd?spm_id_from=333.788.videopod.episodes&vd_source=f93a900f93f134bf44c9945d7d2d9c22&p=66

Spectral Clustering Method:

• Just check slides and the EXAMPLE in class notes

Thank you !!!