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Outline

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

    Linear Algebra for Machine Learning

    Author:Vikash Srivastava
    Topic:Algebra
    Linear Algebra for Machine Learning

    Table of Contents

    • 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
    Next
    Introduction to Linear Algebra

    New Resources

    • Domain of f(x,y)
    • Focus and Directrix
    • Regular Polygons and Equivalent Triangles
    • Untitled
    • The Gardener's Circle

    Discover Resources

    • Pythagoras theorem (expanded)
    • Triangular Prism
    • reflections and rotations - geogebra
    • Comparing Integers
    • ΑΝΑΛΥΣΗ-ΑΛΓΕΒΡΑ

    Discover Topics

    • Congruence
    • Kite
    • Planes
    • Linear Programming or Linear Optimization
    • Confidence Interval
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