This is a tentative schedule.

(Wed, 8/28) Lecture 1: Introduction To ML [administrivia] [slides]

(Wed, 8/28) HW0 Released [written-GradeScope] [written-PDF] [coding]

(Mon, 9/2) Labor Day (No Class)

(Wed, 9/4) Lecture 2: Linear Regression Part 1 [slides]

(Mon, 9/9) Lecture 3: Linear Regression Part 2 [slides]

(Wed, 9/11) Lecture 4: Linear Regression Part 3 [slides]

(Wed, 9/11) HW0 Due / HW1 Released [written-GradeScope] [written-PDF] [coding]

(Mon, 9/16) Lecture 5: Logistic Regression Part 1 [slides]

(Wed, 9/18) Lecture 6: Logistic Regression Part 2 [slides]

Linear Regression Worksheet 1 and Video Walkthrough Released [worksheet] [video]

(Mon, 9/23) Lecture 7: Neural Networks Part 1 [slides]

(Wed, 9/25) Lecture 8: Neural Networks Part 2 [slides]

(Mon, 9/30) Lecture 9: KNNs and Decision Trees Part 1 [slides]

(Wed, 10/2) Lecture 10: Decision Trees Part 2 [see slides above]

(Wed, 10/2) HW1 Due / HW2 Released [written (GradeScope)] [written (PDF)] [coding]

(Mon, 10/7) Lecture 11: K-Means [slides]

(Wed, 10/9) Lecture 12: PCA [slides]

(Mon, 10/14) Midterm 1 Review

(Wed, 10/16) Midterm 1

(Mon, 10/21) Lecture 13: Convolutional Neural Networks Part 1 [slides]

(Wed, 10/23) Lecture 14: Convolutional Neural Networks Part 2 [slides]

(Wed, 10/23) HW2 Due / HW3 Released [written (GradeScope)] [written (PDF)] [coding]

(Mon, 10/28) Lecture 15: Natural Language Processing Part 1 [slides]

(Wed, 10/30) Lecture 16: Natural Language Processing Part 2 [slides]

(Mon, 11/4) Lecture 17: Reinforcement Learning Part 1 [Pre-lecture slides]

(Wed, 11/6) Lecture 18: Reinforcement Learning Part 2

(Wed, 11/6) HW3 Due / HW4 Released

(Mon, 11/11) Lecture 19: Ensembles Part 1

(Wed, 11/13) Lecture 20: Ensembles Part 2

(Mon, 11/18) Lecture 21: Recommender Systems

(Wed, 11/20) Lecture 22: Robust Machine Learning

(Mon, 11/25) Lecture 23: Generative Models

(Wed, 11/27) Friday Schdule (No Class)

(Mon, 12/2) Lecture 24: Ethics

(Wed, 12/4) Midterm 2 Review

(Mon, 12/9) Midterm 2