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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:Krishna Sainath Tulluri, Vikash Srivastava
    Topic:Algebra
    Linear Algebra for Machine Learning
    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

    • Dilation + Rotation of Pentagons
    • Torus
    • Geometric linkage
    • seo tool
    • Untitled

    Discover Resources

    • Número áureo en el pentágono
    • Preface
    • Polar/Rectangular Connection
    • Transforming Exponential Functions with IMAGE Adapted by RH
    • Truss

    Discover Topics

    • Complex Numbers
    • LCM and GCD
    • Percentages
    • Perimeter
    • Interest Calculation
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