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

bookLinear 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.
Tarefa

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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.

Solução

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Seção 1. Capítulo 5

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bookLinear 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.
Tarefa

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.

Solução

Mark tasks as Completed
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Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 1. Capítulo 5
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