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

    Linear Algebra for Machine Learning

    Autor:Vikash Srivastava
    Tema:Algebra
    Linear Algebra for Machine Learning

    Sadržaj

    • 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
    Sljedeće
    Introduction to Linear Algebra

    Novi radovi

    • גיליון אלקטרוני להעלאת נתוני בעיה ויצירת גרף בהתאם
    • Shells
    • Pitfalls of Disk/Washer Method
    • Using Experimental Probability to Estimate π - Monte Carlo Method
    • Prism Drawn in 1-Point Perspective

    Istraži uratke

    • Alice_inblack angle bisector
    • libman
    • Convex lens-Gujarati
    • EMAT_3900_F16_Problem_Set_2_Rectangle_RILEY
    • AOA #4
    • vector addition

    Otkrij teme

    • Sukladnost
    • Eksponent
    • Infinitezimalni račun
    • Valjak
    • Srednje vrijednosti
    O autoruPartneriCentar za pomoć
    Uvjeti korištenjaPrivatnostLicenca
    Grafički kalkulatorKomplet kalkulatoraUradci zajednice

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