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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

    • Parallelogram Anatomy
    • Rolling Circles and Polygons
    • Building Figures with Set Areas
    • Slope Between 2 Points (Phase 2)
    • z`]]

    Discover Resources

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    • Modul 3_Muhammad Arfiyadi Ahsan_SDN Belitung Utara 1
    • Fraktali YIN & YANG
    • Local Linearity

    Discover Topics

    • Conic Sections
    • Logarithm
    • Tangent Line or Tangent
    • Right Triangles
    • Cone
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