Schedule

Week 1: Introduction

Date	Notes	Kaggle Notebooks	Slides	Optional Supplemental Readings	Assignments
2-Oct	Lecture-1	Notebook-1	Week 1	Kaggle CommonLit Readability Competition NIJ Recidivism Challenge

Week 2: Data Preprocessing

Date	Notes	Kaggle Notebooks	Slides	Optional Supplemental Readings	Assignments
9-Oct	Lecture-2a Lecture-2b	Notebook-2a Notebook-2b The {recipes} demo	Week 2	Kuhn & Johnson, Ch. 6 Kuhn & Johnson, Ch. 5 Boehmke & Greenwell, Ch. 3	Assignment 1

Week 3 & Week 4: Introduction to Linear Regression, Bias/Variance Tradeoff, and Cross-validation

Date	Notes	Kaggle Notebooks	Slides	Optional Supplemental Readings	Assignments
16-Oct & 23-Oct	Lecture-3a Lecture-3b	Notebook-3a Notebook-3b Building a Linear Model with caret	Week 3 & 4	Boehmke & Greenwell, Ch. 2 Boehmke & Greenwell, Ch. 4 James et al. Ch.3 Kuhn and Johnson, APM, Ch. 4, 5.1, and Ch.6

Week 5: Regularized Linear Regression

Date	Notes	Kaggle Notebooks	Slides	Optional Supplemental Readings	Assignments
30-Oct	Lecture-4	Notebook-4 Building a Ridge Regression Model Building a Lasso Regression Model Building an Elastic Net Model Using the Prediction Models for a New Text	Week 5	Boehmke & Greenwell, Ch. 6 James et al., Ch.6.2

Week 6 & 7: (Regularized) Logistic Regression

Date	Notes	Kaggle Notebooks	Slides	Optional Supplemental Readings	Assignments
6-Nov & 13-Nov	Lecture-5	Building a Logistic Regression Model Building a Classification Model with Ridge Penalty Building a Classification Model with Lasso Penalty Building a Classification Model with Elastic Net	Week 6 & 7	Boehmke & Greenwell, Ch. 5 James et al., Ch. 4.3 APM, Ch. 12.2 and 12.5	Assignment 2

Week 8: Introduction to K-Nearest Neighbors and Decision Tree Algorithms

Date	Notes	Kaggle Notebooks	Slides	Optional Supplemental Readings	Assignments
20-Nov	Lecture-6a Lecture-6b	Building a Prediction Model with K-nearest neighbors Building a Classification Model with K-nearest neighbors Building a Prediction Model with a Decision Tree Building a Classification Model with a Decision Tree	Week 8_Part 1 Week 8_Part 2	Boehmke & Greenwell, Ch. 8 Boehmke & Greenwell, Ch. 9 APM Ch. 13.5 James et al. Ch. 8.1

Week 9: Introduction to Bagged Trees, Random Forests, and Gradient Boosting Trees

Date	Notes	Kaggle Notebooks	Slides	Optional Supplemental Readings	Assignments
27-Nov	Lecture-7a Lecture-7b			Boehmke & Greenwell, Ch. 10 Boehmke & Greenwell, Ch. 11 Boehmke & Greenwell, Ch. 12 APM Ch. 8 & 14 James et al. Ch. 8.2	Assignment 3