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

    Linear Algebra for Machine Learning

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

    Obsah

    • 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
    Další
    Introduction to Linear Algebra

    Nové materiály

    • Deriving the Arc Length Formula
    • Linear Combination of Vectors
    • Segment Addition Postulate (Mild Questions)
    • Basic and Compound Inequality Illustrator
    • Modifiable Right Triangular Prism

    Objevujte materiály

    • Statistics 2
    • Untitled
    • ML5_2.5
    • สามเหลี่ยมพีทาโกรัส
    • Trying to Circle a Square

    Objevte témata

    • Lineární funkce
    • Určitý integrál
    • Trigonometrické funkce
    • Konstrukce
    • Sinus
    InformacePartneřiHelp centrum
    Podmínky použitíSoukromíLicence
    Grafický kalkulátorSada prostředíVýukové materiály

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