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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

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    • Untitled
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    • Fourier Lissajous (Mechanical)

    Discover Resources

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    • Area of the circle by the triangle or the rectangle
    • Graph JHa 1
    • Cobb-Douglas Function Surface

    Discover Topics

    • Functions
    • Correlation
    • Symmetry
    • Upper and Lower Sum or Riemann Sum
    • Translation
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