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

    Linear Algebra for Machine Learning

    Tekijä:Vikash Srivastava
    Aiheet:Algebra
    Linear Algebra for Machine Learning

    Sisällysluettelo

    • 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
    Seuraava
    Introduction to Linear Algebra

    Uusia resursseja

    • ¿Quién llegará más lejos en el mundial?
    • רישום חופשי
    • Angle Addition: Warm Up Exercises
    • Cartesian vs Polar
    • Viviani's Curve

    Löydä Materiaaleista

    • Graphing Quadratic Equations - Homework 3
    • Demo
    • E is for Emme
    • coplanar and point and lines
    • Ptolemy

    Löydä aiheita

    • Kertolasku
    • Ympäri
    • Sini
    • Derivaatta
    • Tilastot
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