{"categories":["python","numpy"],"url":"https://ryamada.hatenadiary.jp/entry/20141227/1419686856","width":"100%","description":"numpy.linalg\u304c\u305d\u308c\u3002\u3067\u3082\u3001\u3053\u3061\u3089\u306e\u65b9\u304c\u3088\u308a\u5b9f\u8df5\u7684\u304b\u3082\u3002 \u305d\u306e\u69cb\u6210\u306f\uff1a Matrix and vector products Decompositions Matrix eigenvalues Norms and other numbers Solving equations and inverting matrices Exceptions Linear algebra on several matrices at once Matrix and vector products dot product \u30b9\u30ab\u30e9\u30fc\u306e\u666e\u901a\u306e\u7a4d(\u8907\u7d20\u6570\u3082)\u3001\u30d9\u30af\u30c8\u30eb\u306e\u5185\u7a4d\u3001\u884c\u5217\u306e\u901a\u5e38\u306e\u7a4d\u3001\u30a2\u30ec\u30a4\u306e\u5834\u5408\u306f\u3001\u2026","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fryamada.hatenadiary.jp%2Fentry%2F20141227%2F1419686856\" title=\"\u30d1\u30a4\u30bd\u30f3\u3067\u7dda\u5f62\u4ee3\u6570 - ryamada\u306e\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u30fb\u6570\u5b66\u30e1\u30e2\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","blog_title":"ryamada\u306e\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u30fb\u6570\u5b66\u30e1\u30e2","image_url":null,"version":"1.0","title":"\u30d1\u30a4\u30bd\u30f3\u3067\u7dda\u5f62\u4ee3\u6570","provider_url":"https://hatena.blog","published":"2014-12-27 22:27:36","author_name":"ryamada","provider_name":"Hatena Blog","type":"rich","author_url":"https://blog.hatena.ne.jp/ryamada/","blog_url":"https://ryamada.hatenadiary.jp/","height":"190"}