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Linear Algebra for Data Science Using Python

Matrix Operations

Explore fundamental matrix operations such as transpose, inverse, and trace. Understand their mathematical properties and how to compute them using Python's NumPy library to support data science tasks.

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Transpose

A transpose of the matrix Am×nA_{m \times n} is another matrix, An×mTA^T_{n \times m} such that ∀i\forall i, the ithi^{th} row of AA becomes the ithi^{th} column of ATA^T.

Example

A=[123562],AT=[152632]A=\begin{bmatrix}1&2&3\\5&6&2\end{bmatrix} , A^T=\begin{bmatrix}1&5\\2&6\\3&2\end{bmatrix} ...