1.2.12. Week 12 - 11/10

Reading:

• 9. Singular Value Decomposition (SVD)

• 10. Principal Component Analysis (PCA)

New Videos

• Sections 9.0 and 9.1 - Introduction to SVD

• Section 9.2 - How SVD Changes Vectors

• Section 9.3 - Rank from the SVD

• Section 9.4 - Condition Number

• Section 9.5 - Fundamental Matrix Subspaces

• Section 9.6 - Dimensionality Reduction

• Section 9.7 - Over SVD Application - Alternate Projection

• Chapter 10 - PCA

• Chapter 10 - PCA for Recognition

Old Video Lectures:

• Sections 9.0 to 9.3 Introduction to the Singular Value Decomposition - 2024 (23:59)

• Section 9.4 - SVD Dimensionality Reduction - 2024 (19:33)

• Section 9.5 - Four Fundamental Matrix Subspaces - 2024 (6:39)

• Section 9.5 - Four Fundamental Matrix Subspaces (8:37)

• Section 9.6 - Other Applications of SVD - 2024 (10:16)

• Chapter 10 - Principal Component Analysis (PCA) - 2024 (13:30)

• Chapter 10 - Principal Component Analysis (PCA) (18:35)

• Section 10.1 - PCA for Data Analysis - 2024 (10:34)

Assignments:

• Markov Matrix of Land Use

• New Video: Markov Matrix Homework assignment

• Old Video: Markov Matrix Homework assignment (13:03)

• System of Linear ODEs Homework

• New Video: Systems of Linear ODEs Homework assignment

• Old Video: Systems of Linear ODEs Homework assignment

• Attendance Quizzes: AQ08_4, AQ08_5, Week 12 Attendance Quiz Hints