CS-498 Applied Machine Learning

D.A. Forsyth --- 3310 Siebel Center

daf@uiuc.edu, daf@illinois.edu

15:30 - 16:45 OR 3.30 pm-4.45 pm, in old money
1320 Digital Computer Laboratory


Mariya Vasileva mvasile2@illinois.edu

Sili Hui silihui2@illinois.edu

Daeyun Shin dshin11@illinois.edu

Ayush Jain ajain42@illinois.edu

Office Hours:

Ayush Fri - 14h00-16h00 or 2-4 pm, location: in front of 3304

Daeyun Thu - 11h00-13h00 or 11 am-1 pm location: 0207 Siebel/p>

Mariya Wed - 15h00-17h00 or 3 - 5 pm location: 0207 Siebel

Sili Thur - 12h00-14h00 or 12 - 2 pm location: 0207 Siebel

DAF Mon - 14h00-15h00, Fri - 14h00-15h00

or swing by my office (3310 Siebel) and see if I'm busy

Evaluation is by: Homeworks and take home final.

I will shortly post a policy on collaboration and plagiarism



NEWS: NEWS: NEWS: Class meeting on 17 Mar 2016 is CANCELLED (sorry; travel mixup)

Entrance survey

please complete this. I intend it to be anonymous (but don't fully understand google forms, so...) and it will help me know what you know already.

Exit survey

please complete this; I know it's long, but it will help future students. We really want to tune this course right, and this survey will help. I intend it to be anonymous (but don't fully understand google forms, so...) and certainly won't try and find out who filled in what. It's more detailed than the ISIS survey and it will help me know what topics/homework/style/etc worked and what didn't.


Read the textbook. I wrote it specifically for this course, AND it's free. I will split time in lecture between sketching important points described in the text, and solving problems. If you haven't read the text, this might be quite puzzling.

Required Text:

Applied Machine Learning Notes, D.A. Forsyth, (approximate 4'th draft)

Piazza link

for this course

I'm a video star! (or at least, I have been filmed)

Backup Material:

Probability and Statistics for Computer Scientists, D.A. Forsyth, (approximate 12'th draft)


Notes I made in class:

Code fragments I showed in class:

I've cleaned some of these up a bit, but they're not intended to be production code, etc; just to show some R tricks



R resources: