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

    Linear Algebra for Machine Learning

    Author:Krishna Sainath Tulluri, Vikash Srivastava
    Topic:Algebra
    Linear Algebra for Machine Learning
    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

    • Involute of the Circle
    • Intersections of y=a^x and y=log(a, x)
    • Translation of the Graph of a Function
    • 立体几何-公理3及推论
    • Nikmati Keunggulan Di Bandar Judi Terpercaya

    Discover Resources

    • Start, Copy Segment
    • Diagonals of Quadrilaterals II
    • Identifying Rational Functions from Graphs
    • Pyramid x 3 --> Cube
    • Perpendicular Bisectors in a triangle

    Discover Topics

    • Cone
    • Vectors 2D (Two-Dimensional)
    • Interest Calculation
    • Expected Value
    • Vectors
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