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

    Linear Algebra for Machine Learning

    Auteur:Vikash Srivastava
    Onderwerp:Algebra
    Linear Algebra for Machine Learning

    Inhoudstafel

    • 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
    Volgende
    Introduction to Linear Algebra

    Nieuw didactisch materiaal

    • 繪畫垂直線
    • Deriving the Arc Length Formula
    • Midpoint Theorem (V2): Integer Solutions
    • Deciding How New Information Affects Probability
    • Midpoint Theorem Questions: Mild

    Ontdek materiaal

    • Quadrilateral inscribed in circle CM
    • Investigate the sum of interior angles in polygons
    • Caverili's Principle
    • p2a1
    • shayan

    Ontdek onderwerpen

    • Gelijkvormigheidstransformatie of gelijkvormigheid
    • Cosinus
    • Coördinaten
    • Veelhoeken
    • Correlatie
    InfoPartnersHulpcentrum
    GebruiksvoorwaardenPrivacyLicentie
    Grafische rekenmachineRekenmachine suiteCommunity materiaal

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