04/17/2018: Final project is posted. Due May 9 at midnight.
04/04/2018: HW4 is posted. Due April 11.
02/28/2018: Midterm review is posted, see hw folder on Dropbox. Will go over it toady.
02/25/2018: HW3 is posted, due March 7 at the beginning of the class.
02/22/2018: Midterm is on March 7.
02/12/2018: HW 2: Problems 8,9,16-19 from probability notes. Due Feb 21 at beginning of the class. Upload to bb.
01/30/2018: HW 1: Problems 1,2,5,7,14 from notes. Due Feb 7 at beginning of the class.
01/30/2018: Notes for week 1 and 2 are posted.
01/11/2018: Payed summer internship in analytics @ GMU: details. Apply by Feb 15!
12/17/2017: Check back regularly for announcements
Lecture Notes: Will be made available one-day in advance on Bb
Instructor: Vadim Sokolov
Office: Engineering Building, Room 2242
vsokolov(at)gmu.edu
Tel: 703-993-4533
TA: Jungho Park (jpark98@gmu.edu)
Vadim Sokolov: Wed 2:30-4:30pm (at Engineering 2242)
Jungho Park: Mon 1-3pm (at Egnineering 2216)
Location: Planetary Hall 127
Times: 4:30-7:10pm on Wednesday
Grade composition: Grade based on participation in class, in-class midterm, homework assignments, and final project.
Diez, Barr and Cetinkaya-Rundel OpenIntro Statistics, OpenIntro, 2015
James, Witten, Hastie and Tibshirani, An Introduction to Statistical Learning with Applications in R, Springer, 2009.
Hyndman and Athanasopoulos, Forecasting: Principles and Practice, OTexts, 2013.
Additional reading: Data Science Reading List
Airbnb (Random Forest)
Facebook (Decision trees and logistic regrsssion)
Youtube (deep learning)
Uber (time series)