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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
    Thema:Algebra
    Linear Algebra for Machine Learning

    Inhaltsverzeichnis

    • 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
    Weiter
    Introduction to Linear Algebra

    Neue Materialien

    • Parallelogram Anatomy
    • Area of a Trapezoid
    • Building Parallelograms with Set Areas
    • Focus and Directrix
    • Area of a Circle Illustrated

    Entdecke Materialien

    • TrianglesEqual Area
    • The ratio of the areas of two similar triangles
    • Transformation 7
    • Türeve giriş- Eğim fonksiyonu
    • Raio do círculo menor- problema 2
    • สามเหลี่ยมพีทาโกรัส
    • Sudut pada Segiempat Talibusur

    Entdecke weitere Themen

    • Abschnittsweise definierte Funktionen
    • Prozent und Prozentrechnung
    • Zylinder
    • Matrizen
    • Bestimmtes Integral
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