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Section 2.3 Inverse Matrix

You can easily find the inverse of a square matrix \(A\) by A.inverse()

Checkpoint 2.3.1.

Find the inverse of the matrix.
\begin{equation*} A = \begin{bmatrix} 1 & -1 & 0\\ 1 & 0 & -1\\ -6 & 2 & 3 \end{bmatrix} \end{equation*}
How to find the inverse of a square matrix? that is, to find another matrix \(B\) such that
\begin{equation*} AB=BA=I_n \end{equation*}
Let \(B=[\beta_1\,\beta_2\,\ldots\, \beta_n]\) and \(I_n=[\mathbf{e}_1\ \mathbf{e}_2\ \ldots\ \mathbf{e}_n]\text{.}\) \(AB=I_n\) can be read as
\begin{equation*} AB=A[\beta_1\,\beta_2\,\ldots\, \beta_n]=[A\beta_1\, A\beta_2\ ,\ldots, \ A\beta_n]=[\mathbf{e}_1,\mathbf{e}_2,\ldots, \mathbf{e}_n], \end{equation*}
which can be read as \(n\)-linear systems. What we do to solve \(n\)-linear systems together?
What is the nature of invertibility of a square matrix? You can think it is the generalization of nonzero numbers.