{"id":46540,"date":"2023-03-16T15:34:50","date_gmt":"2024-02-01T03:27:24","guid":{"rendered":"https:\/\/www.silicloud.com\/zh\/blog\/46540-2\/"},"modified":"2024-04-29T19:09:24","modified_gmt":"2024-04-29T11:09:24","slug":"46540-2","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/zh\/blog\/46540-2\/","title":{"rendered":""},"content":{"rendered":"

\u30c7\u30d5\u30a9\u30eb\u30c8\u306eJupyter notebook\u306b\u30b9\u30cb\u30da\u30c3\u30c8(\u30b7\u30e7\u30fc\u30c8\u30ab\u30c3\u30c8)\u547c\u3073\u51fa\u3057\u306e\u62e1\u5f35\u6a5f\u80fd\u3092\u8ffd\u52a0\u3057\u3001\u751f\u7523\u6027\u3092\u3042\u3052\u305f\u8a71\u3067\u3059\u3002<\/p>\n

\u4ee5\u4e0b\u306e\u9806\u306b\u6cbf\u3063\u3066\u8a18\u3057\u3066\u3044\u304d\u307e\u3059\u3002<\/p>\n

    \n
  1. \n
      \u524d\u63d0\u3068\u306a\u308b\u74b0\u5883<\/ol>\n<\/li>\n<\/ol>\n

       <\/p>\n

        \n
      1. \n
          \u62e1\u5f35\u30c4\u30fc\u30eb\u306e\u5c0e\u5165(jupyter_contrib_nbextensions)<\/ol>\n<\/li>\n<\/ol>\n

           <\/p>\n

            \n
          1. \n
              \u30c7\u30d5\u30a9\u30eb\u30c8\u30b9\u30cb\u30da\u30c3\u30c8\u306e\u4f7f\u7528<\/ol>\n<\/li>\n<\/ol>\n

               <\/p>\n

                \u30aa\u30ea\u30b8\u30ca\u30eb\u30b9\u30cb\u30da\u30c3\u30c8\u306e\u767b\u9332<\/ol>\n

                \u524d\u63d0\u3068\u306a\u308b\u74b0\u5883<\/h1>\n

                \u81ea\u5b85\u3067\u4f7f\u3063\u3066\u3044\u308bMacBooK Air\u3092\u7528\u3044\u307e\u3059\u3002<\/p>\n

                2011 MacBook Air 3,1\r\n1.4 GHz Intel Core 2 Duo\r\n2 GB 1067 MHz DDR3\r\n128 GB SSD\r\nHigh Sierra 10.13.2\r\n<\/code><\/pre>\n
                \u307e\u305f\u3001pyenv 1.1.5 + anaconda3-4.0.0\u3067Jupiter notebook\u306e\u74b0\u5883\u3092\u5b9f\u73fe\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n
                \u62e1\u5f35\u30c4\u30fc\u30eb\u306e\u5c0e\u5165(jupyter_contrib_nbextensions)<\/h1>\n
                \u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3078\u306e\u63a5\u7d9a\u3084\u3001matplotlib\u3067\u306e\u30b0\u30e9\u30d5\u306e\u66f8\u304d\u65b9\u306a\u3069\u3001\u983b\u7e41\u306b\u4f7f\u7528\u3059\u308b\u304c\u4e00\u304b\u3089\u66f8\u304d\u305f\u304f\u306a\u3044\u3082\u306e\u306f\u30b9\u30cb\u30da\u30c3\u30c8\u5316\u3057\u3066\u3001\u3059\u3050\u306b\u547c\u3073\u51fa\u305b\u308b\u3088\u3046\u306b\u3059\u308b\u3068\u697d\u3067\u3059\u3002<\/p>\n
                \u3053\u308c\u3092\u5b9f\u73fe\u3059\u308b\u305f\u3081\u306b\u3001jupyter_contrib_nbextensions\u3092\u7528\u3044\u307e\u3059\u3002
                \nhttps:\/\/github.com\/ipython-contrib\/jupyter_contrib_nbextensions<\/p>\n
                ~$ <\/span>conda install<\/span> -c<\/span> conda-forge jupyter_contrib_nbextensions\r\n<\/code><\/pre>\n
                \u4e0a\u8a18\u30b3\u30de\u30f3\u30c9\u3092\u5b9f\u884c\u3057\u305f\u3089\u3001Jupyter notebook\u3092\u7acb\u3061\u4e0a\u3052\u3001\u4e0b\u8a18\u306b\u30a2\u30af\u30bb\u30b9\u3057\u307e\u3057\u3087\u3046\u3002(\u304a\u4f7f\u3044\u306e\u74b0\u5883\u306b\u3088\u3063\u3066\u9069\u5b9c\u8aad\u307f\u66ff\u3048\u3066\u304f\u3060\u3055\u3044\u3002)<\/p>\n
                localhost:8888\/nbextensions\r\n<\/code><\/pre>\n
                \u3059\u308b\u3068\u3053\u306e\u3088\u3046\u306a\u753b\u9762\u304c\u7acb\u3061\u4e0a\u304c\u308a\u307e\u3059<\/p>\n
                \"\u30b9\u30af\u30ea\u30fc\u30f3\u30b7\u30e7\u30c3\u30c8<\/div>\n
                \u3053\u306e\u4e2d\u304b\u3089\u5fc5\u8981\u305d\u3046\u306a\u3082\u306e\u3092\u9078\u3073\u30c1\u30a7\u30c3\u30af\u30dc\u30c3\u30af\u30b9\u3092\u3064\u3051\u307e\u3059\u3002\u305d\u308c\u305e\u308c\u306e\u8aac\u660e\u306f\u4e0b\u306e\u65b9\u306b\u3061\u3083\u3093\u3068\u66f8\u3044\u3066\u3042\u308a\u307e\u3059\u306e\u3067\u3001\u305d\u308c\u3092\u8aad\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
                \u304a\u3059\u3059\u3081\u306f\u4e0b\u8a18\u3067\u3059\u3002<\/p>\n
                  \n
                • \n
                    Nbextensions dashboard tab(\u307b\u307c\u5fc5\u9808\u3002Extensions\u306e\u30bf\u30d6\u3092\u65b0\u3057\u304f\u8ffd\u52a0\u3057\u3066\u304f\u308c\u308b\u3002)<\/ul>\n<\/li>\n<\/ul>\n
                     <\/p>\n
                      \n
                    • \n
                        Snippets Menu(\u30b9\u30cb\u30da\u30c3\u30c8\u3092\u767b\u9332\u3059\u308b\u306e\u306b\u7528\u3044\u308b)<\/ul>\n<\/li>\n<\/ul>\n
                         <\/p>\n
                          ExecuteTime(\u30bb\u30eb\u3054\u3068\u306e\u5b9f\u884c\u6642\u9593\u3092\u793a\u3057\u3066\u304f\u308c\u308b)<\/ul>\n
                          \u4ed6\u306b\u3082\u4f7f\u3048\u308b\u62e1\u5f35\u306f\u305f\u304f\u3055\u3093\u3042\u308a\u307e\u3059\u3002\u305f\u3060\u6b32\u5f35\u3063\u3066\u305f\u304f\u3055\u3093\u5165\u308c\u3059\u304e\u308b\u3068Jupyter notebook\u306e\u8d77\u52d5\u304c\u9045\u304f\u306a\u308a\u307e\u3059\u306e\u3067\u305d\u3053\u306f\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n
                          \u30c7\u30d5\u30a9\u30eb\u30c8\u30b9\u30cb\u30da\u30c3\u30c8\u306e\u4f7f\u7528<\/h1>\n
                          \u3055\u3066\u3001\u4e0a\u8a18\u306e\u62e1\u5f35\u306e\u30c1\u30a7\u30c3\u30af\u30dc\u30c3\u30af\u30b9\u3092\u3064\u3051\u305f\u3089\u3001<\/p>\n
                          localhost:8888\/tree\r\n<\/code><\/pre>\n
                          \u306b\u623b\u308a\u9069\u5f53\u306a\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u958b\u3044\u3066\u304f\u3060\u3055\u3044\u3002\u4e0b\u8a18\u306e\u3088\u3046\u306b\u30b9\u30cb\u30da\u30c3\u30c8\u306e\u30bf\u30d6\u304c\u5897\u3048\u3066\u3044\u308b\u306e\u304c\u5206\u304b\u308b\u304b\u3068\u601d\u3044\u307e\u3059\u3002<\/p>\n
                          \"\u30b9\u30af\u30ea\u30fc\u30f3\u30b7\u30e7\u30c3\u30c8<\/div>\n
                          \u3053\u306e\u3046\u3061New array of given shape\u3092\u9078\u3073\u307e\u3059\u3068\u3001\u30bb\u30eb\u4e0a\u306b\u4e0b\u8a18\u306e\u3088\u3046\u306b\u66f8\u304b\u308c\u307e\u3059\u3002<\/p>\n
                          \"\u30b9\u30af\u30ea\u30fc\u30f3\u30b7\u30e7\u30c3\u30c8<\/div>\n
                          \u30c7\u30d5\u30a9\u30eb\u30c8\u3067\u767b\u9332\u3055\u308c\u3066\u3044\u308b\u3082\u306e\u3067\u3082\u3001\u304b\u306a\u308a\u4f7f\u3048\u307e\u3059\u306e\u3067\u662f\u975e\u4f7f\u7528\u3057\u3066\u307f\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n
                          \u30aa\u30ea\u30b8\u30ca\u30eb\u30b9\u30cb\u30da\u30c3\u30c8\u306e\u767b\u9332<\/h1>\n
                          \u3055\u3066\u672c\u984c\u3067\u3059\u3002\u81ea\u5206\u3060\u3051\u306e\u30b9\u30cb\u30da\u30c3\u30c8\u3092\u767b\u9332\u3059\u308b\u624b\u9806\u306b\u3064\u3044\u3066\u8a18\u3057\u307e\u3059\u3002<\/p>\n
                          \u307e\u305a\u3001~\/.jupyter\/custom\/custom.js\u3092\u7de8\u96c6\u3057\u3001\u30b5\u30f3\u30d7\u30eb\u306e\u30b9\u30cb\u30da\u30c3\u30c8\u3092\u52a0\u3048\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
                          ~$ <\/span>mkdir<\/span> ~\/.jupyter\/custom\/ & touch<\/span> ~\/.jupyter\/custom\/custom.js\r\n~$ <\/span>vim ~\/.jupyter\/custom\/custom.js\r\n<\/code><\/pre>\n
                          require<\/span>([<\/span>\"<\/span>nbextensions\/snippets_menu\/main<\/span>\"<\/span>],<\/span> function<\/span> (<\/span>snippets_menu<\/span>)<\/span> {<\/span>\r\n    console<\/span>.<\/span>log<\/span>(<\/span>'<\/span>Loading `snippets_menu` customizations from `custom.js`<\/span>'<\/span>);<\/span>\r\n    var<\/span> my_favorites<\/span> =<\/span> {<\/span>\r\n        '<\/span>name<\/span>'<\/span> :<\/span> '<\/span>My favorites<\/span>'<\/span>,<\/span>\r\n        '<\/span>sub-menu<\/span>'<\/span> :<\/span> [<\/span>\r\n            {<\/span>\r\n                '<\/span>name<\/span>'<\/span> :<\/span> '<\/span>Menu item text<\/span>'<\/span>,<\/span>\r\n                '<\/span>snippet<\/span>'<\/span> :<\/span> [<\/span>'<\/span>new_command<\/span>'<\/span>,],<\/span>\r\n            },<\/span>\r\n            {<\/span>\r\n                '<\/span>name<\/span>'<\/span> :<\/span> '<\/span>Another menu item<\/span>'<\/span>,<\/span>\r\n                '<\/span>snippet<\/span>'<\/span> :<\/span> [<\/span>'<\/span>another_new_command<\/span>'<\/span>,],<\/span>\r\n            },<\/span>\r\n        ],<\/span>\r\n    };<\/span>\r\n    snippets_menu<\/span>.<\/span>options<\/span>[<\/span>'<\/span>menus<\/span>'<\/span>].<\/span>push<\/span>(<\/span>snippets_menu<\/span>.<\/span>default_menus<\/span>[<\/span>0<\/span>]);<\/span>\r\n    snippets_menu<\/span>.<\/span>options<\/span>[<\/span>'<\/span>menus<\/span>'<\/span>].<\/span>push<\/span>(<\/span>my_favorites<\/span>);<\/span>\r\n    console<\/span>.<\/span>log<\/span>(<\/span>'<\/span>Loaded `snippets_menu` customizations from `custom.js`<\/span>'<\/span>);<\/span>\r\n});<\/span>\r\n<\/code><\/pre>\n
                          Jupyter notebook\u3092\u518d\u8d77\u52d5\u3057\u3001\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u958b\u304f\u3068\u4e0b\u8a18\u306e\u753b\u9762\u306e\u3088\u3046\u306b\u300cMy favorites\u300d\u3068\u3044\u3046\u30b9\u30cb\u30da\u30c3\u30c8\u304c\u5897\u3048\u3066\u3044\u308b\u306f\u305a\u3067\u3059\u3002<\/p>\n
                          \"\u30b9\u30af\u30ea\u30fc\u30f3\u30b7\u30e7\u30c3\u30c8<\/div>\n
                          \u3055\u3066\u305d\u308c\u3067\u306f\u3001\u4eca\u5ea6\u306f\u3053\u308c\u3092\u66f8\u304d\u63db\u3048\u3001\u6a5f\u68b0\u5b66\u7fd2\u3078\u306e\u30b9\u30cb\u30da\u30c3\u30c8\u3092\u5165\u308c\u3066\u898b\u307e\u3057\u3087\u3046\u3002<\/p>\n
                          require<\/span>([<\/span>\"<\/span>nbextensions\/snippets_menu\/main<\/span>\"<\/span>],<\/span> function<\/span> (<\/span>snippets_menu<\/span>)<\/span> {<\/span>\r\n    console<\/span>.<\/span>log<\/span>(<\/span>'<\/span>Loading `snippets_menu` customizations from `custom.js`<\/span>'<\/span>);<\/span>\r\n    var<\/span> my_favorites<\/span> =<\/span> {<\/span>\r\n        '<\/span>name<\/span>'<\/span>:<\/span> '<\/span>My favorites<\/span>'<\/span>,<\/span>\r\n        '<\/span>sub-menu<\/span>'<\/span>:<\/span> [<\/span>\r\n            {<\/span>\r\n                '<\/span>name<\/span>'<\/span> :<\/span> '<\/span>LogisticRegression<\/span>'<\/span>,<\/span>\r\n                '<\/span>snippet<\/span>'<\/span> :<\/span> [<\/span>\r\n                    \"<\/span>from sklearn.linear_model import LogisticRegression<\/span>\"<\/span>,<\/span>\r\n                    \"<\/span>lr = LogisticRegression()<\/span>\"<\/span>,<\/span>\r\n                    \"<\/span>lr.fit(X_train, y_train)<\/span>\"<\/span>,<\/span>\r\n                    \"<\/span>print(lr.score(X_test, y_test))<\/span>\"<\/span>,<\/span>\r\n                    \"<\/span>y_predict = lr.predict(X_test)<\/span>\"<\/span>,<\/span>\r\n                ],<\/span>\r\n            },<\/span>\r\n            {<\/span>\r\n                '<\/span>name<\/span>'<\/span> :<\/span> '<\/span>SGDClassifier<\/span>'<\/span>,<\/span>\r\n                '<\/span>snippet<\/span>'<\/span> :<\/span> [<\/span>\r\n                    \"<\/span>from sklearn.linear_model import SGDClassifier<\/span>\"<\/span>,<\/span>\r\n                    \"<\/span>sgd = SGDClassifier(loss=<\/span>\\\"<\/span>hinge<\/span>\\\"<\/span>, penalty=<\/span>\\\"<\/span>l2<\/span>\\\"<\/span>)<\/span>\"<\/span>,<\/span>\r\n                    \"<\/span>sgd.fit(X_train, y_train)<\/span>\"<\/span>,<\/span>\r\n                    \"<\/span>print(sgd.score(X_test, y_test))<\/span>\"<\/span>,<\/span>\r\n                    \"<\/span>y_predict = sgd.predict(X_test)<\/span>\"<\/span>\r\n                ],<\/span>\r\n            },<\/span>\r\n        ],<\/span>\r\n    };<\/span> \r\n    snippets_menu<\/span>.<\/span>options<\/span>[<\/span>'<\/span>menus<\/span>'<\/span>].<\/span>push<\/span>(<\/span>snippets_menu<\/span>.<\/span>default_menus<\/span>[<\/span>0<\/span>]);<\/span>\r\n    snippets_menu<\/span>.<\/span>options<\/span>[<\/span>'<\/span>menus<\/span>'<\/span>].<\/span>push<\/span>(<\/span>my_favorites<\/span>);<\/span>\r\n    console<\/span>.<\/span>log<\/span>(<\/span>'<\/span>Loaded `snippets_menu` customizations from `custom.js`<\/span>'<\/span>);<\/span>\r\n});<\/span>\r\n<\/code><\/pre>\n
                          \u3053\u306e\u3088\u3046\u306b\u66f8\u304d\u63db\u3048\u308b\u3053\u3068\u3067\u3001\u30b9\u30cb\u30da\u30c3\u30c8\u3092\u767b\u9332\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n
                          \"\u30b9\u30af\u30ea\u30fc\u30f3\u30b7\u30e7\u30c3\u30c8<\/div>\n
                          JavaScript\u3067\u767b\u9332\u3059\u308b\u306e\u304c\u82e5\u5e72\u9762\u5012\u3067\u3059\u306e\u3067\u3001\u50d5\u306f\u3044\u3064\u3082\u4e0b\u8a18\u306e\u3088\u3046\u306b\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n
                            \n
                          1. \n
                              \u767b\u9332\u3057\u305f\u3044\u30b9\u30cb\u30da\u30c3\u30c8\u3092\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306b\u66f8\u304d\u8fbc\u3093\u3067\u4fdd\u5b58<\/ol>\n<\/li>\n<\/ol>\n
                               <\/p>\n
                                \n
                              1. \n
                                  \u4fdd\u5b58\u3055\u308c\u305fipynb\u5f62\u5f0f\u306e\u30d5\u30a1\u30a4\u30eb\u3092\u30a8\u30c7\u30a3\u30bf\u3067\u958b\u304d\u8a72\u5f53\u90e8\u5206\u3092\u30b3\u30d4\u30fc<\/ol>\n<\/li>\n<\/ol>\n
                                   <\/p>\n
                                    \n
                                  1. \n
                                      custom.js\u306b\u30da\u30fc\u30b9\u30c8<\/ol>\n<\/li>\n<\/ol>\n
                                       <\/p>\n
                                        \n
                                      1. \n
                                          \u30da\u30fc\u30b9\u30c8\u3057\u305f\u90e8\u5206\u306e\u6539\u884c\u8a18\u53f7\u3092\u524a\u9664<\/ol>\n<\/li>\n<\/ol>\n
                                           <\/p>\n
                                            \u5b8c\u6210<\/ol>\n
                                            \u4ee5\u4e0a\u3001\u30b9\u30cb\u30da\u30c3\u30c8\u3092\u6d3b\u7528\u3057\u305f\u6a5f\u68b0\u5b66\u7fd2\u6848\u4ef6\u306e\u751f\u7523\u6027\u5411\u4e0a\u3067\u3057\u305f\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
                                            \u30c7\u30d5\u30a9\u30eb\u30c8\u306eJupyter notebook\u306b\u30b9\u30cb\u30da\u30c3\u30c8(\u30b7\u30e7\u30fc\u30c8\u30ab\u30c3\u30c8)\u547c\u3073\u51fa\u3057\u306e\u62e1\u5f35\u6a5f\u80fd\u3092\u8ffd\u52a0\u3057\u3001\u751f\u7523\u6027\u3092 […]<\/p>\n","protected":false},"author":9,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-46540","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"\n- Blog - Silicon Cloud<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.silicloud.com\/zh\/blog\/46540-2\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:description\" content=\"\u30c7\u30d5\u30a9\u30eb\u30c8\u306eJupyter notebook\u306b\u30b9\u30cb\u30da\u30c3\u30c8(\u30b7\u30e7\u30fc\u30c8\u30ab\u30c3\u30c8)\u547c\u3073\u51fa\u3057\u306e\u62e1\u5f35\u6a5f\u80fd\u3092\u8ffd\u52a0\u3057\u3001\u751f\u7523\u6027\u3092 […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.silicloud.com\/zh\/blog\/46540-2\/\" \/>\n<meta property=\"og:site_name\" content=\"Blog - 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