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2026-08-25
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1
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Welcome + Introduction
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Syllabus | Server Instructions (html) | Notes (html)
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2026-08-27
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1
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Statistical Learning
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Notes (html)
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Lab | Lab Script
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2026-09-01
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2
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Linear Regression
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Notes (html)
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Lab | Lab Script
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2026-09-03
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2
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Linear Regression
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Homework 1 – ggplot2
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2026-09-08
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3
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KNN + Classification
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Notes (html)
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2026-09-10
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3
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Logistic Regression
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Homework 2 – Regression
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2026-09-15
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4
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LDA
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Homework 3 – Polynomial Regression
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2026-09-17
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4
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QDA, KNN
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Lab | Lab Script
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2026-09-22
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5
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Model Assessment
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Notes (html)
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Homework 4 – Classification
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2026-09-24
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5
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Cross Validation
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2026-09-29
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6
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Cross Validation
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2026-10-01
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6
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Cross Validation
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Lab | Lab Script
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2026-10-06
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7
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GitHub + Project Info
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Notes (html)
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Homework 5 – Cross Validation
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2026-10-08
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7
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Guest Lecture
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2026-10-13
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8
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Exam Review
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2026-10-15
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8
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Midterm Exam
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2026-10-20
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9
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Model Selection + Shrinkage
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Notes (html)
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2026-10-22
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9
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Dimension Reduction
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Lab | Lab Script
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2026-10-27
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10
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PCR & PLS
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Homework 6 – Regularization and Model Selection
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2026-10-29
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10
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Moving Beyond Linearity + Regression Splines
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Notes (html)
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Lab | Lab Script
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2026-11-03
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11
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GAMs
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Homework 7 – Dimension Reduction
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2026-11-05
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11
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Tree-Based Methods
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Notes (html)
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Lab | Lab Script
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2026-11-10
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12
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Bagging, Random Forests, and Boosting
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Homework 8 – Non-linear Models
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2026-11-12
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12
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Bagging + Boosting + Random Forests
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Lab | Lab Script
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2026-11-17
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13
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SVM
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Notes (html)
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Homework 9 –Tree-Based Models
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2026-11-19
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13
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SVM
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2026-11-24
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14
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Thanksgiving Break
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2026-11-26
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14
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Thanksgiving Break
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2026-12-01
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15
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Unsupervised Learning
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Notes (html)
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Homework 10 – Support Vector Machines | Lab | Lab Script
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2026-12-03
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15
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Unsupervised Learning
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2026-12-08
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16
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Project Presentations
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2026-12-10
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16
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Project Presentations
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