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Contenuti

  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

    Nuove risorse

    • z`]]
    • רישום חופשי
    • Graphs of Rational Expressions
    • Slope Between 2 Points (Phase 2)
    • Untitled

    Scopri le risorse

    • basic math
    • QUY TẮC ĐẾM
    • Rectangle, Lily Brinkman
    • Law of Sines (M8-I5 #5)
    • Similarity Part 1

    Scopri gli argomenti

    • Segmenti
    • Funzioni esponenziali
    • Vettori 3D (tridimensionali)
    • Istogramma
    • Rapporti
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