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

    Linear Algebra for Machine Learning

    Autor:Vikash Srivastava
    Téma:Algebra
    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

    • רישום חופשי
    • apec
    • Pythagorean Theorem: Extension Exercises
    • Perpendicular Lines: Quick Exploration
    • Congruent Sides & Angles in △s: Exploration

    Objevujte materiály

    • Dodecahedron Half 1 Dome
    • Direct & Inverse Variation
    • Quadrilateral Snapper
    • Direction cosines of a vector
    • Exploring functions of 2 variables

    Objevte témata

    • Elipsa
    • Kvádr
    • Funkce
    • Posunutí
    • Matice
    InformacePartneřiHelp centrum
    Podmínky použitíSoukromíLicence
    Grafický kalkulátorSada prostředíVýukové materiály

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