Merge pull request #20 from hhchen1105/main

Correct a typo: 'Vecrtors => Vectors'

The-Art-of-Linear-Algebra-zh-CN.tex

@@ -591,7 +591,7 @@ $A$的每一个列向量都可以用$Q$和上三角矩阵$R$重新构造出.
 
 
 \begin{itemize}
-  \item 7.1节 (p.259) Singular Values and Singular Vecrtors
+  \item 7.1节 (p.259) Singular Values and Singular Vectors
 \end{itemize}
 
 包括长方阵在内的所有矩阵都具有奇异值分解(SVD). 
@@ -692,4 +692,4 @@ Ashley Fernandes 在排版时帮我美化了这篇论文, 使它更加一致和
   \end{figure}
 \end{enumerate}
 
-\end{document}
+\end{document}

The-Art-of-Linear-Algebra.tex

@@ -598,7 +598,7 @@ Note that Pattern 4 (P4) is working for the decomposition.
 
 
 \begin{itemize}
-  \item Sec.7.1 (p.259) Singular Values and Singular Vecrtors
+  \item Sec.7.1 (p.259) Singular Values and Singular Vectors
 \end{itemize}
 
 Every matrix (including rectangular one) has a singular value decomposition (SVD).
@@ -711,4 +711,4 @@ traditional data science and machine learning. An important part of the matrix w
 
 \end{enumerate}
 
-\end{document}
+\end{document}