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

Reuse

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