{"type":"rich","provider_url":"https://hatena.blog","author_name":"sy4310","url":"https://www.eureka-moments-blog.com/entry/2018/09/15/Glossary_of_Machine_Learning","author_url":"https://blog.hatena.ne.jp/sy4310/","height":"190","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fwww.eureka-moments-blog.com%2Fentry%2F2018%2F09%2F15%2FGlossary_of_Machine_Learning\" title=\"\u6a5f\u68b0\u5b66\u7fd2\u306e\u57fa\u672c\u7528\u8a9e\u96c6 - EurekaMoments\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","provider_name":"Hatena Blog","published":"2018-09-15 11:11:22","version":"1.0","categories":["Machine Learning","Book"],"blog_url":"https://www.eureka-moments-blog.com/","description":"\u76ee\u6b21 \u76ee\u6b21 \u306f\u3058\u3081\u306b \u7279\u5fb4\u91cf(Feature Value) \u5b66\u7fd2(Learning) \u6559\u5e2b\u3042\u308a / \u306a\u3057\u5b66\u7fd2(Supervised / Unsupervised Learning) \u6700\u9069\u5316\u554f\u984c(Optimization Problem) \u5ea7\u6a19\u964d\u4e0b\u6cd5(Coordinate Descent) \u6700\u6025\u964d\u4e0b\u6cd5(Gradient Descent) \u78ba\u7387\u52fe\u914d\u6cd5(Stochastic Gradient Descent) \u6c4e\u5316\u6027\u80fd(Generalization Ability) \u65b0\u3057\u3044\u7279\u5fb4\u91cf\u3092\u4f5c\u308b(Creating New Feature Value) \u591a\u5c64\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af(Maltilayer Neur\u2026","image_url":"https://images-fe.ssl-images-amazon.com/images/I/51CziILeS9L._SL160_.jpg","blog_title":"EurekaMoments","width":"100%","title":"\u6a5f\u68b0\u5b66\u7fd2\u306e\u57fa\u672c\u7528\u8a9e\u96c6"}