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Kapitel

  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

    • Basic and Compound Inequality Illustrator
    • Laundry Basket
    • Linear Equation Graphs: Thin Slice
    • Midpoint Theorem (V2): Integer Solutions
    • Congruent Sides & Angles in △s: Exploration

    Entdecke Materialien

    • Algebra 1
    • Construction of Phi^2
    • Anil 2
    • L3_09
    • TUGAS 1 7A YUDHA 00

    Entdecke weitere Themen

    • Erwartungswert
    • Vektoren 2D (zweidimensional)
    • Sekante
    • Trigonometrische Funktionen oder Winkelfunktionen
    • Parallelogramm
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