Please use the homework template to submit homework's (compile to pdf format. If you have not used Latex before, you may find \url{https://pangea.stanford.edu/computing/unix/formatting/latexexample.php} helpful for getting started.
The notes will be due to Rafael, Nick, and myself (via email) one week after the lecture (by 10 am that day).
Assigned reading:
Assigned reading:
Assigned reading:
[Kairavi's and Julian's tex files]
(Th January 30 1:30PM) [Lecture6 Slides] [Howework 3] [Howework 3 Solutions] [Thurs scribe notes]
Assigned reading:
[Lecture8 Slides] [scribe notes] [Howework 4] [Homework 4 Solutions]
Assigned reading:
Take home exam 1 will cover material up to this point! You MAY NOT work together on the take home exam.
[Howework 5] [Homework 5 Solutions]
Exam One has been posted to blackboard. Good luck and remember you cannot work with others!
Please read Chapter 8 on regression and classification trees.
[Howework 6] [Howework 6 Solutions] [Howework 6 Code]
[Lecture16 Slides] [scribe notes]
Take home exam 2 will cover material up to this point! You MAY NOT work together on the take home exam. Take home exam two will be posted to blackboard on Friday March 28 and will be due at 11:59 pm on Friday April 4. Please follow the instructions as posted on the exam. Please see class emails for clarification questions on the take home exam. There have been no typos found thus far.
(Tues April 1 1:30PM)
[Howework 8] [Howework 8 Solutions]
Tues Jan 14 | 1. Introduction and why multivariate models? | |
Thurs Jan 16 | 2. More about multivariate models | |
Tues Jan 21 | 3. More about multivariate models | |
Thurs Jan 23 | 4. Contour plots and Intro to PCA. | |
Tues Jan 28 | 5. PCA | |
Thurs Jan 30 | 6. PCA | |
Tues Feb 4 | 7. Factor Analysis | |
Thurs Feb 6 | 8. Factor Analysis | |
Tues Feb 11 | 9. Introduction to classification methods. | |
Thurs Feb 13 | 10. LDA and QDA | |
Tues Feb 18 | 11. Introduction to Regression and Classification Trees | |
Thurs Feb 20 | 12. No class: Take home exam | |
Tues Feb 25 | 13. No class: office hours | |
Thurs Feb 27 | 14. No class: take home exam | |
Tues Mar 4 | 15. Classification Trees | |
Thurs Mar 6 | 16. Bootstrapping and Bagging | |
Tues Mar 11 | (Spring break, no class) | |
Thurs Mar 13 | (Spring break, no class) | |
Tues Mar 18 | 17. Random Forests | |
Thurs Mar 20 | 18. Intro to Clustering . | |
Tues Mar 25 | 19. Intro to Clustering II | |
Thurs Mar 27 | 20. No class | |
Tues Apr 1 | 21. R Lab | |
Thurs Apr 3 | 22. R Lab | |
Tues Apr 8 | 23. Intro to Bayesian Analysis | |
Thurs Apr 10 | (Spring carnival, no class) | |
Tues Apr 15 | 24. Intro to Bayesian Analysis | |
Thurs Apr 17 | 25. Intro to Gibbs Sampling | |
Tues Apr 22 | 26. Bayesian special topics: TBD | |
Thurs Apr 24 | 27. Bayesian special topics: TBD | |
Tues Apr 29 | 28.Bayesian special topics:TBD | |
Thurs May 1 | 29. | TBD |