矩阵论笔记：奇异值分解SVD(Singular Value Decomposition)以及应用总结！

<div class="tags-box space">
<span class="label">所属专栏：</span>
<a class="tag-link" href="https://blog.csdn.net/column/details/33085.html" target="_blank">机器学习</a>

</div>
</div>
<div class="operating">
</div>
</div>
</div>

版权声明：本文为博主原创文章，引用时请附上链接。          https://blog.csdn.net/abc13526222160/article/details/88562191        </div>
<link rel="stylesheet" href="https://csdnimg.cn/release/phoenix/template/css/ck_htmledit_views-f57960eb32.css">
<div id="content_views" class="markdown_views prism-dracula">
<!-- flowchart 箭头图标 勿删 -->
<svg xmlns="http://www.w3.org/2000/svg" style="display: none;">
<path stroke-linecap="round" d="M5,0 0,2.5 5,5z" id="raphael-marker-block" style="-webkit-tap-highlight-color: rgba(0, 0, 0, 0);"></path>
</svg>
<div class="table-box"><table><tbody><tr><td bgcolor="black"><font size="3" color="yellow">奇异值分解SVD(Singular Value Decomposition)以及应用总结！</font></td></tr></tbody></table></div>