Course Materials

• Syllabus
• Linear Algebra: Foundations of Machine Learning
  • Part 1 (Chapters 0-9)
  • Part 2 (Chapters 10-16)
  • Part 3a (Chapters 17-20)
  • Errata
• Homework Submission Guide
• Math Prelim Exam

Schedule

• Week 1
  • Lectures this week are online; see e-mail from the instructor for a Zoom link.
  • Tu 1/18: Notation, linearity, and field axioms (0 - 1.5) [slides]
  • Th 1/20: Norms, dot products, and multiplication (1.6 - 1.8)
  • Homework 1: Due Monday, 1/31 before 5pm
    • bioe210_test_suite.m
    • lasso_data.mat
    • Solutions
• Week 2
  • Tu 1/25: Matrix multiplication (2)
  • Th 1/27: Rotation and translation (3)
  • Homework 2: Due Monday, 1/31 before 5pm
    • Solutions
• Week 3
  • Tu 2/1: Gaussian Elimination (4)
  • Th 2/3: Finite difference method (5)
    • No lecture on 2/3. Read chapter 5 and complete these practice problems (answers included).
  • Homework 3: Due Monday, 2/7 before 5pm
    • Solutions
• Week 4
  • Tu 2/8: Matrix inverses (6)
  • Th 2/10: Rank and solvability (7)
  • Homework 4: Due Monday, 2/14 before 5pm
    • Solutions
• Week 5
  • Tu 2/15: Exam 1
  • Th 2/17: no class
  • Homework 5: Due Monday, 2/28 before 5pm
• Week 6
  • Tu 2/22: Linear models I (8.1-8.3)
  • Th 2/24: Linear models II (8.4-8.6, 9.3-9.4) [notes]
  • Homework 6: Due Wednesday, 3/2 before 5pm
    • MLX file
    • HW6_data.mat
    • Solutions
• Week 7
  • Tu 3/1: Linear models III (9)
    • Applied Linear Regression in Matlab
      • MLX file
      • hospital_records.mat
  • Th 3/3: Root finding (10)
  • Homework 7: Due Monday, 3/7 before 5pm
    • MLX file
    • HW7_data.mat
    • Solutions
• Week 8
  • Tu 3/8: Optimization and convexity (11)
  • Th 3/10: Gradient descent (12)
    • MLX file for examples in the textbook
  • Homework 8: Due Monday, 3/21 before 5pm
    • Solutions
• Week 9
  • Spring Break
• Week 10
  • Tu 3/22: Logistic regression (13)
    • MLX file and MAT file for gradient descent example
  • Th 3/24: Cross validation, bias, and variance (14.1-14.4)
  • Homework 9: Due Monday, 3/28 before 5pm
    • cas9.mat
    • Solutions
• Week 11
  • Tu 3/29: Exam 2 (Chapters 8-14.4)
  • Th 3/31: Regularization (14.5) & Geometry (15)
  • Homework 10: Due Monday, 4/11 before 5pm
    • MLX file
    • HW10_data.mat
    • Solutions
• Week 12
  • Tu 4/5: Support Vector Machines (16)
  • Th 4/7: Basis vectors and orthogonality (17)
  • Homework 11: Due Monday, 4/11 before 5pm
    • HW11_data.mat
    • Solutions
• Week 13
  • Tu 4/12: Eigenvalues and eigenvectors (18)
  • Th 4/14: Eigendecomposition (19.1)
  • Homework 12: Due Monday, 4/18 before 5pm
    • Solutions
• Week 14
  • Tu 4/19: Singular Value Decomposition (19.2-19.3)
  • Th 4/21: Low rank approximations (20.1)
    • SVD review slides
    • Image compression slides
  • Homework 13: Due Monday, 4/25 before 5pm
    • Solutions
• Week 15
  • Tu 4/26: Principal Component Analysis [slides]
    • PCA Guide
  • Th 4/28: Recommender systems (20.2)
  • Homework 14: Due Monday, 5/2 before 5pm
• Week 16
  • Tu 5/3: Exam 3
    • SVM study guide
    • Basis study guide
    • Eigenvalue/eigenvector study guide