Course Content

Getting into NumPy Basics

# 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:

: Computes the`dot()`

**dot product**of two arrays;:`transpose()`

**Transposes**an array;: Computes the`inv()`

**inverse**of a matrix;: Performs the`linalg.svd()`

**singular value decomposition**of a matrix;: Determines the`linalg.eig()`

**eigenvalues**and**eigenvectors**of a matrix.

Task

**Compute**the dot product of the arrays.**Transpose**the first array.**Compute**the inverse of the second array.

Task

**Compute**the dot product of the arrays.**Transpose**the first array.**Compute**the inverse of the second array.

Everything was clear?

`NumPy`

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

: Computes the`dot()`

**dot product**of two arrays;:`transpose()`

**Transposes**an array;: Computes the`inv()`

**inverse**of a matrix;: Performs the`linalg.svd()`

**singular value decomposition**of a matrix;: Determines the`linalg.eig()`

**eigenvalues**and**eigenvectors**of a matrix.

Task

**Compute**the dot product of the arrays.**Transpose**the first array.**Compute**the inverse of the second array.