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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

    • Riemann Sums
    • z`]]
    • Nikmati Keunggulan Di Bandar Judi Terpercaya
    • Vertical and Oblique Asymptote
    • Combining Random Variables

    Discover Resources

    • Monte Carlo simulation of throwing darts to estimate pi
    • Grospoint
    • Math Topics Project 1
    • Inv 2.2C - Congruent Triangles
    • Relative Font Size
    • Fundamental Theorem, Riemann Sums, and Accumulation

    Discover Topics

    • Secant Line or Secant
    • General Quadrilateral
    • Optimization Problems
    • Median Value
    • Linear Functions
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