Course Schedule

Class Date Day Topic Reading (Pre-Class) Notes
1 Aug 23 Tue Introduction Pre-Req material; R and Rstudio
Modern Data Science with R sections: 2,3,4,6,7,9
HW 0 assigned; Get textbook(s); update software; review pre-req material
2 Aug 25 Thu R and Tidyverse
Linear Regression with R
R Tidyverse
3-8, 10-11, 12.3, 12.5, 15, 17-19, 20.1-20.4, 21.1-21.5, 23.4, 27-29
ISL 3.1-3.6
R formula interface
3 Aug 30 Tue Supervised Learning I ISL 1, 2.1, 7.1
ESL 1, 2.1-2.4
HW 0 Due
supervised_1.R
4 Sep 01 Thu Supervised Learning II ISL 2.2-2.3
ESL 2.5-2.9
supervised_2.R
5 Sep 06 Tue Resampling: Bootstrap and Splines ISL 5.2, 7.2-7.4
ESL 7.11, 5.1-5.3
(optional) Bootstrapping Regression Models
HW 1 Due
6 Sep 08 Thu Resampling: Cross-Validation and Model Selection ISL 5.1
ESL 7.10
ISL Chap 3 (review)
7 Sep 13 Tue Penalized Regression ISL 6.1-6.2
ESL 3.3-3.4
HW 2 Due
8 Sep 15 Thu Penalized Regression ISL 6.4-6.5 (optional 6.3)
ESL 3.5-3.6
9 Sep 20 Tue Classification ISL 4.1-4.3
ESL 4.1-4.4
HW 3 Due
10 Sep 22 Thu Classification ESL 9.1
11 Sep 27 Tue Density Estimation IPSUR: pg. 209-218 (MLE intro)
Maximum Likelihood Estimation: pg. 221-223
IPSUR Chap. 5-7 (Random Variable Review, if necessary)
HW 4 Due
12 Sep 29 Thu Review
Oct 04 Tue No Class
13 Oct 06 Thu Density Estimation Silverman 2.1-2.6
14 Oct 11 Tue Clustering Primary: ISL 12.4-12.5; ITDM 7.1; 7.5
Secondary: ESL 14.3.1-14.3.8; 14.3.12; ITDM 7.2-7.3
HW 5 Due
15 Oct 13 Thu Clustering Primary: ESL 8.5.1
Secondary: Gaussian Mixture Models: 11.1-11.3
16 Oct 18 Tue Generative Classifiers ISL 4.4-4.5; ESL 6.6 HW 6 Due
17 Oct 20 Thu Support Vector Machines (SVM) ISL 9.1-9.6
ESL 12.1-12.3 or MMDS 12.3
18 Oct 25 Tue Tree-Based Methods ISL 8.1, 8.3.1-8.3.2
ESL 9.2
HW 7 Due
19 Oct 27 Thu Tree-Based Methods ISL 8.2, 8.3.3-8.3.4
ESL 15
20 Nov 01 Tue Ensembles ISL 8.2 HW 8 Due
21 Nov 03 Thu Boosting ISL 8.2.3; ESL 10.1-10.9
LogitBoost paper
Nov 08 Tue No Class
22 Nov 10 Thu Boosting ESL 10.10-10.14
XGBoost paper, CatBoost paper, LightGBM
23 Nov 15 Tue Feature Engineering ISLR 6.3 HW 9 Due
24 Nov 17 Thu Review
25 Nov 22 Tue Association Analysis MMDS 6.1; ITDM 5.1-5.2, 5.7
Instacart Case
HW 10 Due
Nov 24 Thu No Class
26 Nov 29 Tue Association Analysis ESL 14.2; MMDS 6.2; ITDM 5.3,5.8
27 Dec 01 Thu Networks Network Science (Chapter 2)
Statistical Analysis of Network Data with R (Chapter 2)
McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a Feather: Homophily in Social Networks.
28 Dec 06 Tue Networks MMDS 5.1-5.3, 5.5 HW 11 Due
Dec 14 Wed (12pm/noon) Final Project Due