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Lära Linear Algebra Operations | Getting into NumPy Basics
Getting into NumPy Basics
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Getting into NumPy Basics

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

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