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Outline

  1. Linear Algebra for Machine Learning
    1. Introduction to Vectors
    2. Introduction to Matrices

    Linear Algebra for Machine Learning

    Author:Vikash Srivastava
    Topic:Algebra
    Linear Algebra for Machine Learning

    Table of Contents

    • Introduction to Vectors

      • Introduction to Linear Algebra
      • What is a vector ?
      • Introduction to Vectors
      • Scaling Vectors
      • Vector Addition
      • Adding Vectors Geometrically
      • Vector Subtraction
      • Dot Product Insight
      • Vector Projections
      • Orthogonality Illustrated
      • Cross Product Insight
      • Vector Norms
    • Introduction to Matrices

      • Theory of Matrices
      • Determinant of a matrix
      • Inverse of a matrix
      • Eigenvalues & Eigenvectors
    Next
    Introduction to Linear Algebra

    New Resources

    • Squaring a Rectangle (PST Version)
    • Odd Function Explorer
    • Segment Addition Postulate (Mild Questions)
    • Writing and Graphing Proportional Relationships (k>0)
    • Linear Equation Graphs: Thin Slice

    Discover Resources

    • Equilateral triangle
    • Napoleon's Theorem - Defining Hypotheses and Thesis
    • rhtjrfmyj
    • ckat path
    • Slope

    Discover Topics

    • Expected Value
    • Pie Chart or Circle Chart
    • Correlation
    • Calculus
    • Secant Line or Secant
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