Weekly plans and update for week 46

Dear All, we hope you are all doing well and staying healthy. 

First, and perhaps most importantly, we are still allowed to have the in-person labs. We will let you know asap if this changes.

Else, last week we discussed ensemble methods like boosting, bagging, voting and random forests. 

On Thursday we will wrap up our discussion on gradient boosting with further examples during the first lecture. For the second lecture on Thursday (115pm-2pm) 

Iwe will have a guest lecturer, John Aiken, who is an expert on applications of gradient boosting and xgboost applied to social sciences. John recently defended his thesis, where the primary focus was on boosting methods applied to data from the social sciences.

On Friday we start with our second-last topics: Support Vector Machines for classification and regression.

Recommended literature before the lectures are:

Geron's chapter 5. Chapter 12 (sections 12.1-12.3 are the most relevant ones)  of Hastie et al contains also a good discussion.

The following overview video on Support Vector Machines may also be of interest https://www.youtube.com/watch?v=efR1C6CvhmE&ab_channel=StatQuestwithJoshStarmer. see also this video":"https://www.youtube.com/watch?v=N1vOgolbjSc&ab_channel=AliceZhao.

The first lecture on Thursday is devoted to a summary from last week, with additional examples. This material is included in the lectures from week 45, see also Hastie *et al.* chapter 10.1-10.10.

Project 3 will be available either Thursday or Friday this week.

Best wishes to you all,

the FYS-STK gang.