Mathematics for Data Science (IMEN 891I)

Overview

Course Objectives

This course covers some mathematical topics that will be useful to study modern data science. The course is for engineers and practitioners; (measure-theoretic) rigorous statements and long proofs will be omitted.

Lecture Slides

• Chapter 1: Basic Linear Algebra [Slides]

• Chapter 2: Matrix Decompositions [Slides]

• Chapter 3: Orthogonal Projection [Slides]

• Chatper 4: Basic Probability and Statistics [Slides]

• Chatper 5: Convergence of Random Variables and Probability Distributions [Slides]

• Chatper 6: Basic Concentration Inequalities [Slides]

• Chapter 7: Convex Analysis and Optimization [Slides]

• 2023 Fall Lecture slides are updated.
  [Chapter 1] [Chapter 2] [Chapter 3] [Chapter 4] [Chapter 5] [Chapter 6] [Chapter 7]

Lecture Videos

• Lecture 1 (Chapter 1)

• Lecture 2 (Chapter 1 & 2)

• Lecture 3 (Chapter 2)

• Lecture 4 (Chapter 2)

• Lecture 5 (Chapter 2 & 3)

• Lecture 6 (Chapter 3)

• Lecture 7 (Chapter 3)

• Lecture 8 (Chapter 3 & 4)

• Lecture 9 (Chapter 4)

• Lecture 10 (Chapter 4)

• Lecture 11 (Chapter 4)

• Lecture 12 (Chapter 4 & 5)

• Lecture 13 (Chapter 5)

• Lecture 14 (Chapter 5)

• Lecture 15 (Chapter 5)

• Lecture 16 (Chapter 5)

• Lecture 17 (Chapter 5 & 6)

• Lecture 18 (Chapter 6)

• Lecture 19 (Chapter 6)

• Lecture 20 (Chapter 6 & 7)

• Lecture 21 (Chapter 7)

• Lecture 22 (Chapter 7)