Before the first class meeting, read Chapter 1 Why Git? Why GitHub? of Happy Git With R.
Read the chapter Software for modeling.
Read as needed Happy Git and GitHub for the useR
Start Chapters 1 and 2 in Introduction to Statistics in R on DataCamp—Due Jan 20 NLT 5:00 PM
Sign-up for a free account on GitHub. When you register for a free individual GitHub account, request a student discount to obtain a few private repositories as well as unlimited public repositories. Please use something similar to FirstNameLastName as your username when you register with GitHub. For example, my username on GitHub is alanarnholt. If you have a popular name such as John Smith, you may need to provide some other distinguishing characteristic in your username.
Send an email to arnholtat@appstate.edu with a Subject line of STT3860 - GitHub Username, and tell me in the body of your email your first name, last name, and your GitHub username.
Make sure RStudio is set up to communicate with Git by following the directions in HappyGitWithR for introducing yourself to Git.
Cache your credentials and set up a personal access token (PAT) by following the directions in HappyGitWithR.
TL;DR the chapters in Happy Git With R — follow this document to Set up Git and GitHub
Optional Resources:
Read the chapter A Tidyverse Primer.
Start Chapters 3 and 4 in Introduction to Statistics in R on DataCamp—Due Jan 24 NLT 5:00 PM
Read the chapter A Review of R Modeling Fundamentals.
Start reproduction of Introduction to Statistics in R - Due Feb 3 NLT 5:00 PM
Finish reproduction of Introduction to Statistics in R - Due Feb 3 NLT 5:00 PM
Read the chapter The Ames Housing Data.
Read Chapters 1-5 of Correlation and Regression
Start Chapters 1 and 2 in Modeling with Data in the Tidyverse on DataCamp—Due Feb 7 NLT 5:00 PM
Read the chapter Spending our Data.
Start Chapters 3 and 4 in Modeling with Data in the Tidyverse on DataCamp—Due Feb 14 NLT 5:00 PM
Misc Regression topics
Read the chapter Fitting Models with parsnip
Read Appendix E.
Start reproduction of Modeling with Data in the Tidyverse - Due Feb 24 NLT 5:00 PM
In class review this document.
Finish reproduction of Modeling with Data in the Tidyverse - Due Feb 24 NLT 5:00 PM
Read the chapter A Model Workflow
Start Chapters 1 and 2 in Modeling with Tidymodels in R on DataCamp—Due Feb 28 NLT 5:00 PM
Read the chapter Feature Engineering with recipes
Start Chapters 3 and 4 in Modeling with Tidymodels in R on DataCamp—Due Mar 7 NLT 5:00 PM
Start reproduction of Modeling with Tidymodels in R - Due Mar 24 NLT 5:00 PM
Read the chapter Judging Model Effectiveness
Work on reproduction of Modeling with Tidymodels in R - Due Mar 24 NLT 5:00 PM
Finish reproduction of Modeling with Tidymodels in R - Due Mar 24 NLT 5:00 PM
Read the chapter Resampling for Evaluating Performance
Pick data for group project #1 from modeldata package. Data must have at least 8 variables and 1,000 or more rows. Accept group project here. Group presentations will be April 1.
Group presentations for project #1 - Apr 1.
Read the chapter Comparing Models with Resampling
Read Chapters 2-4 in Tree based Models in R
Start Chapters 1 and 2 in Machine Learning with Tree Based Models in R on DataCamp—Due Apr 7 NLT 5:00 PM
Review as needed Train and Test
Review as needed Regression Trees
Review as needed Predictive Model Building
Read the chapter Model Tuning and the Dangers of Overfitting
Read Chapters 5-6 in Tree based Models in R
Start Chapters 3 and 4 in Machine Learning with Tree Based Models in R on DataCamp—Due Apr 14 NLT 5:00 PM
Start reproduction of Machine Learning with Tree Based Models in R - Due Apr 21 NLT 5:00 PM
Review as needed Train and Test
Review as needed Regression Trees
Review as needed Predictive Model Building
Read the chapter Grid Search
Work on reproduction of Machine Learning with Tree Based Models in R - Due Apr 21 NLT 5:00 PM
Finish reproduction of Machine Learning with Tree Based Models in R - Due Apr 21 NLT 5:00 PM
Pick data for group project #2 from modeldata package. Data must have at least 8 variables and 1,000 or more rows. Accept group project here. Group presentations will be May 6 during the final exam period.