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개요

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

    Linear Algebra for Machine Learning

    저자:Vikash Srivastava
    주제:대수
    Linear Algebra for Machine Learning

    목차

    • 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
    다음
    Introduction to Linear Algebra

    새 자료

    • Fourier Lissajous (Mechanical)
    • Nikmati Keunggulan Di Bandar Judi Terpercaya
    • seo tool
    • z`]]
    • Rolling an Equilateral Triangle

    자료 찾기

    • Dynamic Witch of Agnesi
    • Munns window
    • quiz square of numbers 25 to 75
    • Copy a Segment
    • rot jocas B anticlepsidra

    주제 찾기

    • 타원
    • 유리수
    • 원뿔곡선
    • 평면 도형
    • 확대
    정보파트너십지원 센터
    서비스 조항개인 정보라이선스
    그래픽 계산기계산기 스위트커뮤니티 자료

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