• Linear Algebra Textbook
  • Table of Contents
    • Chapter 1
      • Introduction to Matrices and Linear Systems
    • Chapter 2
      • Deep Dive into Linear Algebra
    • Chapter 3
      • Beyond Linear Algebra
  • 1 Introduction to Matrices and Linear Systems
    • 1.1 Linear Geometry: Vectors in Space and Angle & Length
      • Vectors in Space
      • Vector Length
      • Angle between Vectors
    • 1.2 Dot Product
    • 1.3 Solving Linear Equations
      • Gauss’s Method
    • 1.4 Row Echelon Form & Reduced Row Echelon Form
      • 1.4.1 Reduced Row Echelon Form
      • Equivalence Relations
      • Linear Combination Lemma
      • Supporting Theorems
    • 1.5 Labs
    • 1.6 Coding Labs
    • 1.7 Projects
  • 2 Deep Dive into Linear Algebra
    • 2.1 Definition of Vector Space
      • Extend to \(\mathbb{R^{n}}\)
      • Subspaces
      • Complex Numbers
      • Subspaces & Spanning Sets
      • Solutions to Assorted Problems:
    • 2.2 Linear Independence, Basis, Dimension
      • Linear Independence
      • Basis
      • Dimension
      • Fundamental Subspaces
      • Solutions to Assorted Problems:
    • 2.3 Orthogonal Matrices, Change of Basis
      • Orthogonal Vector
      • Orthogonal Vector
      • Orthogonal Matrix
      • Orthonormal Basis
    • 2.4 Projection and Change of Basis
      • Projection:
      • Projection into Subspaces:
      • Example:
      • The Gram-Schmidt Process:
      • Example:
    • 2.5 Labs
    • 2.6 Coding Labs
  • 3 Beyond Linear Algebra
  • 4 References
    • 4.1 Linear Algebra Resource Board
    • 4.2 R Programming Resources
  • Published with bookdown

Linear Algebra

4 References

4.1 Linear Algebra Resource Board

  • MIT OpenCourseWare: Linear Algebra by Professor Strang

  • 3Blue1Brown: The Essence of Linear Algebra

  • Khan Academy: Linear Algebra

  • Linear Algebra Companion by Professor Shemanske

4.2 R Programming Resources

  • RStudio Education

  • R for Data Science

  • A Gentle Introduction to Tidy Statistics in R

  • R Markdown

  • Data Camp: R Programming Tutorials Playlist