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

    Linear Algebra for Machine Learning

    Auteur :Krishna Sainath Tulluri, Vikash Srivastava
    Thème :Algèbre
    Linear Algebra for Machine Learning
    Linear Algebra for Machine Learning

    Table des matières

    • 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
    Suivant
    Introduction to Linear Algebra

    Nouvelles ressources

    • רישום חופשי
    • Equation of Locus - Parabola
    • apec
    • Circle Passing Through 3 Points
    • Triangle with 3 Right Angles

    Découvrir des ressources

    • Parameter Changes to Parent Functions #2 - MHS
    • Untitled
    • Ed Southall (18th February, Probability)
    • LP Example 2
    • W18/1 Square

    Découvrir des Thèmes

    • Continuité
    • Nombres Rationnels
    • Triangles Scalènes
    • Cercle Inscrit ou Circonscrit
    • Moyennes
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