Part 1 · Chapter 2

Linear Algebra Essentials

Develops the vector, matrix, geometric, and decomposition tools used to represent engineering data and understand machine learning algorithms.

Chapter map

What this chapter develops

  • Vectors and matrices
  • Vector spaces and basis
  • Norms and distance
  • Projections
  • Eigenvalues and eigenvectors
  • Singular value decomposition

Engineering practice

Application and Diamond Examples

  1. 01

    Diamond examples connect matrix structure to engineering and ML throughout the chapter

Companion materials

Portal resources

Chapter catalogFind this chapter’s indexed examples and related topics.
Python notebooksNo companion AE notebooks are currently assigned to this chapter.None
AE datasetsNo companion AE datasets are currently assigned to this chapter.None
DiscussionAsk chapter-specific questions and compare engineering interpretations with other readers.