Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Lære Linear Algebra Operations | Getting into NumPy Basics
Getting into NumPy Basics
course content

Kursinnhold

Getting into NumPy Basics

book
Linear Algebra Operations

NumPy offers a plethora of functions for executing linear algebra operations on arrays, including matrix multiplication, transposition, inversion, and decomposition. Key functions include:

  • dot(): Computes the dot product of two arrays;
  • transpose(): Transposes an array;
  • inv(): Computes the inverse of a matrix;
  • linalg.svd(): Performs the singular value decomposition of a matrix;
  • linalg.eig(): Determines the eigenvalues and eigenvectors of a matrix.
Oppgave

Swipe to start coding

  1. Compute the dot product of the arrays.
  2. Transpose the first array.
  3. Compute the inverse of the second array.

Løsning

Mark tasks as Completed
Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 1. Kapittel 5
Vi beklager at noe gikk galt. Hva skjedde?
some-alt