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Contenuti

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

    Linear Algebra for Machine Learning

    Autore:Vikash Srivastava
    Argomento:Algebra
    Linear Algebra for Machine Learning

    Sommario

    • 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
    Successivo
    Introduction to Linear Algebra

    Nuove risorse

    • Tetrahedron String Art
    • Area Between Two Curves
    • Untitled
    • Visualizing the Pythagorean Identity with Sine and Cosine
    • 兩位數的位值

    Scopri le risorse

    • Circumference and diameter
    • Function Test
    • Construct a Copy of a Segment
    • title
    • TUGAS MODUL3_TAUFIK ALBAR_GARIS TINGGI

    Scopri gli argomenti

    • Pitagora o teorema di Pitagora
    • Esponenti
    • Curve parametriche
    • Aritmetica
    • Calcolo differenziale
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