Week 01: Introduction, Review & Feature Selection

Complete the Class Survey before 11:59pm on Tuesday

Class Survey dataset is available here

Tuesday
PPT: Introduction

Complete before next class

Skim through ISLR2 Chapters 1-5, if you have not read the book previously!

Zestimate

Zillow Research

A Visual Introduction to Linear Regression (Machine Learning University by Amazon)

Seeing Theory - See Chapters on Regression, Variance, ANOVA, Probabilities, etc, for a visual and interactive review

The Importance of Data Splitting (Machine Learning University by Amazon)

The Bias Variance Tradeoff (Machine Learning University by Amazon)

Optional

RTutor: Refresh your R skills using AI!

ML comic strip (Google Cloud)

Thursday

PPT: ML Review

Lab: ML Review Template (ML Review Solution)

Data: zillow23.xlsx

Complete before next class

ISLR2 Chapter 6.1: Subset Selection

ISLR2 Chapter 6.2: Shrinkage Methods

A Visual Introduction to Logistic Regression (Machine Learning University by Amazon)

Linear Model Selection and Best Subset Selection (13:44)

Forward Stepwise Selection (12:26)
Backward Stepwise Selection (5:26)

Estimating Test Error Using Mallow’s Cp, AIC, BIC, Adjusted R-squared (14:06)

Lab: Best Subset Selection (10:36)*
Lab: Forward Stepwise Selection and Model Selection Using Validation Set (10:32)*

Lab: Model Selection Using Cross-Validation (5:32)*

*If you're checking your work against solutions posted by the authors, you might get slightly different numbers, because you're using a newer version of R.

Optional
Statistics vs. Data Science (4:00)

The Illustrated Machine Learning Website

Friday
PPT: Subset Selection

Lab: Subset Selection with Zillow

Complete before next class

ISLR2 Chapter 6.2: Shrinkage Methods

Estimating Test Error Using Cross-Validation (8:44)
The Ridge (12:37)
The Lasso (15:22)
Tuning Parameter Selection for Ridge Regression and Lasso (5:27)

Lab: Ridge Regression and Lasso (16:34)