There is no class 11/21 because of the Thanksgiving holiday, see the University calendar.
Feel free to reach out if you have any questions/concerns about your paper/project. I will be in town and on email :)
Just posted readings for the rest of the semester as requested :)
For those thinking of using lasso in their project, please see
- The McNeish paper we read - The ISLR book we read, section 6.5 for R code examples using glmnet - Older code using glmpath: http://members.cbio.mines-paristech.fr/~jvert/svn/tutorials/practical/linearclassification/linearclassification.R
Readings are up for next week :) Following up on class discussion yesterday, here is the paper that I thought of assigning but was concerned about overloading people: https://www.microsoft.com/en-us/research/wp-content/uploads/2016/05/Bishop-MBML-2012.pdf This is not assigned, but it's an excellent paper and feedback is welcome. Also, someone asked about Gaussian processes yesterday. In thinking about the whole context of that discussion, I thought it might be helpful to recap some terminology. A random process is something that creates non-deterministic (uncertain) outcome Examples: Rolling dice (fair dice or not) Flipping a coin (fair coin or not) Random sampling Counterexamples Flipping a coin with two heads (because there is only 1 outcome, it is deterministic/certain) A random variable maps the outcome of a random process to a number. Example: Flipping a coin Random process: flipping a coin Random variable X where 1 is heads and 0 is tail...
Greetings 😃 If you haven't already gone through the welcome post , please do so now. I've put up the readings for next week (see tab above). You will need your UoM email id/password to log in (e.g. foobar@memphis.edu would log in as foobar). I've also created a refresher video for the Kaggle kernel lab we did yesterday. We will keep working with that kernel in our lab next week:
I've put up the readings for next week (see tab above). You will need your UoM email id/password to log in (e.g. foobar@memphis.edu would log in as foobar). One of the readings is what's called a "scrolly." As you scroll down, it will run animations that accompany the text. You can also scroll up to reverse the animations. Scrolling up and down might be particularly helpful (like instant replay). Make sure your respond with your comments by 9/18 at noon. Make your comments by replying/commenting to this post (the one you are looking at now).
Just posted readings for the rest of the semester as requested :)
ReplyDeleteFor those thinking of using lasso in their project, please see
- The McNeish paper we read
- The ISLR book we read, section 6.5 for R code examples using glmnet
- Older code using glmpath: http://members.cbio.mines-paristech.fr/~jvert/svn/tutorials/practical/linearclassification/linearclassification.R