검색
Google Classroom구글 클래스룸
GeoGebra지오지브라 클래스룸

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

    • רישום חופשי
    • Dilation + Rotation of Pentagons
    • Kite Function Art
    • Untitled
    • Converting Between Degrees and Radians

    자료 찾기

    • Linear Functions (practice)
    • COMPLEXOS - suma de complexos
    • HG2b
    • Area of a triangle - change apex, height, base

    주제 찾기

    • 히스토그램
    • 평균
    • 자연수
    • 작도
    • 특징점
    정보파트너십지원 센터
    서비스 조항개인 정보라이선스
    그래픽 계산기계산기 스위트커뮤니티 자료

    앱을 여기에서 다운로드하세요:

    Download_on_the_App_Store_Badge_US-UK_RGB_blk_4SVG_092917

    © 2025 GeoGebra®