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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

    • Rotating Custom Polygons Around an Axis
    • Angle Addition Postulate (V2) - Integer Solutions
    • Segment Addition Postulate (Mild Questions)
    • Conditional Probability in Two-Way Tables
    • Rotating Plane Figures to Form Solids

    Entdecke Materialien

    • Probability Simulator
    • Leonard T 10
    • kite
    • Coordinate Geometry: Quick Investigation
    • Sum of angles of quadrilaterals

    Entdecke weitere Themen

    • Vektoren 3D (dreidimensional)
    • Median
    • Funktionen
    • Normalverteilung
    • Terme
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