Course Notes and Assignments

Spring 2019
Tuesdays & Thursdays, 09:00-10:15
JSPN G24

Instructor: Taylor Arnold
E-mail: tarnold2@richmond.edu
Office: Jepson Hall, Rm 218
Office Hours: See below
Syllabus: STAT389_Syllabus.pdf

GitHub Classroom: Information and links
Office Hours: Make an appointment
Piazza Site: View and post questions
DateNotes
2019-01-15 Class 01: Statistical Learning
[solutions01.pdf]
Installing R
2019-01-17 Class 02: Simple Linear Regression
[solutions02.pdf]
[class02.Rmd]
2019-01-22 Class 03: Matrix Computations and Multivariate Regression
[solutions03.pdf]
2019-01-24 Class 04: Normal Equations
[class04.Rmd]
[solutions04.pdf]
[class04-solutions.html]
2019-01-29 no class
2019-01-31 Class 05: Singular Value Decomposition
[class05.Rmd]
[solutions05.pdf]
[class05-solutions.html]
2019-02-05 EXAM I
[take-home question]
2019-02-06 Class 06: Ridge Regression.
[class06.Rmd]
[solutions06.pdf]
[class06-solutions.html]
2019-02-12 Class 07: Lasso Regression.
[class07.Rmd]
[class07-solutions.html]
[solutions07.pdf]
2019-02-14 Class 08: Text Analysis
[class08.Rmd]
[class08-solutions.html]
[solutions08.pdf]
2019-02-19 Class 09: Logistic Regression
[supplementary derivation]
[class09.Rmd]
[class09-solutions.html]
[solutions09.pdf]
2019-02-21 Class 10: More Text Prediction
[class10.Rmd]
[class10-solutions.html]
2019-02-26 EXAM II
[take-home question]
[take-home code]
2019-02-28 Class 11: Splines and KNN
[lab11.Rmd]
2019-02-28 [Finish and submit lab11.Rmd]
2019-03-07 Class 12: Dimensionality and GAMS
[lab12.Rmd]
[lab12-solutions.html]
2019-03-19 Class 13: Trees
[lab13.Rmd]
[lab13-solutions.html]
2019-03-21 Class 14: Images
[lab14.Rmd]
[lab14-solutions.html]
2019-03-26 Class 15: Dense Neural Networks
[lab15.Rmd]
[lab15-solutions.html]
2019-03-28 Class 16: Training Neural Networks
[lab16.Rmd]
[solutions16.pdf]
[lab16-solutions.html]
2019-04-02 Class 17: Dense Neural Networks for Image Data
[lab17.Rmd]
[lab17-solutions.html]
2019-04-04 Class 18: Regularizing and Training Dense Neural Networks
[lab18.Rmd]
[lab18-solutions.html]
2019-04-09 EXAM III
[take home only; no class; exam due April 11]
[exam03.Rmd]
2019-04-11 Class 19: Towards Convolutions
[LeNet]
[lab19.Rmd]
2019-04-16 Class 20: Transfer Learning I
[lab20.Rmd]
[lab20-solutions.html]
2019-04-18 Class 21: Transfer Learning II
2019-04-23 Final Project Workshop
2019-04-24 Final Project Due (5pm) instructions
Data processing example
2019-04-25 EXAM IV
[take-home questions]
2019-04-25 Final Project Presentations [Attendance required!]