Introduction to Machine Learning

by Albert Major

Why Linear Algebra Matters

• Linear algebra = mathematics of data.
• Used in almost all modern data analysis and AI methods.
• Key areas where it appears:
  • Neural networks: completely based on linear algebra.
  • Linear regression (studied in statistics): built on linear algebra.
  • Dimensionality reduction (reducing predictors): relies on linear algebra.
  • Projection techniques: also linear algebra.
• Will appear again in many later courses.
• Goal of the course: get everyone to the same level, regardless of high school background.

Topics Covered in the Course

• Vectors
• Matrices
• Systems of linear equations (how to solve them)
• Linear transformations
• Eigenvectors and eigenvalues
• Determinants
• Vector spaces
• Orthogonality

Level of Difficulty

• Designed so anyone with high school math can follow.