Material for NCSU Statistical Learning Group (SLG) presentations, Fall 2014
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
00-Post
01-Gaines
02-Day
03-Burton
04-Grantham
05-Mehrotra
06-Winkel
07-Jackson
08-Naughton
09-Peng
README.md

README.md

Statistical Learning Group, Fall 2014

SLG is a reading group at North Carolina State University organized by Dr. Justin Post and PhD Statistics students Jami Jackson, Brian Gaines, Neal Grantham, and Josh Day.

Goals of the group

  1. Introduce advanced topics in data mining, machine learning, and other 'active' areas of statistics in order to broaden our knowledge base and, where possible, connect statistical ideas.
  2. Offer opportunities to present upper level topics and improve presentation and teaching ability with a focus on audience of the presentation and data visualizations.
    • There will be 10 presentations made in fall 2014 (see below).
    • Presenting 'mentors' will be available for the presenters.
  3. Give outlets for presentation, writing, and computing that are available for prospective employers to view.
    • Each presentation will be recorded and made available (if ok'd by presenter).
    • Write-ups and code will also be available.
  4. Improve applied analysis skills and coding.
    • Every presentation will include an analysis or simulation aspect with code available for all members to work with.

Introduction

Watch Neal's introduction to SLG here and see Overview.pdf in 00-Post, Justin's slides on an introduction to statistical learning (Sadly, Justin's talk is not available online because the video camera battery died halfway through, but we've learned our lesson!).

Schedule of talks

Talk Date Topic Presenter(s)
00 09/05/14 Introduction Neal Grantham & Justin Post
01 09/19/14 Regularization & Penalization Brian Gaines
02 09/26/14 Penalization Methods Joshua Day
03 10/03/14 Grouped & Adaptive LASSO Will Burton
10/10/14 Fall Break
04 10/17/14 Classification Neal Grantham
05 10/24/14 Bayesian Classification Suchit Mehrotra
06 10/31/14 Decision Trees Munir Winkel
07 11/07/14 Support Vector Machines Jami Jackson
08 11/14/14 Ranking via SVMs Brian Naughton
09 11/21/14 Discriminant Analysis Huimin Peng
Done for the semester