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

    Linear Algebra for Machine Learning

    Autore:Vikash Srivastava
    Argomento:Algebra
    Linear Algebra for Machine Learning

    Sommario

    • 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
    Successivo
    Introduction to Linear Algebra

    Nuovi materiali

    • Angle Addition Postulate (V2) - Integer Solutions
    • Squaring a Rectangle (PST Version)
    • Odd Function Explorer
    • 繪畫垂直線
    • Right Triangle Inscribed in a Semicircle

    Scopri i materiali

    • Quadrilateral Centres of Mass
    • Flower shape from 5 points on a polar coordinate plane
    • dy rotation
    • Construction of Parallel Lines
    • Circle Rolling on Circle (without slip)

    Scopri gli argomenti

    • Rotazione
    • Triangoli equilateri
    • Funzioni polinomiali
    • Circonferenza
    • Pitagora o teorema di Pitagora
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