{"id":477756,"date":"2023-08-09T09:19:52","date_gmt":"2023-08-09T09:19:52","guid":{"rendered":""},"modified":"2023-09-05T11:15:22","modified_gmt":"2023-09-05T11:15:22","slug":"jupyter","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/jp\/wiki\/jupyter\/","title":{"rendered":"\u30b8\u30e5\u30d4\u30bf\u30fc"},"content":{"rendered":"

Jupyter (\u65e7\u79f0 IPython) \u306f\u3001\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6 \u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0\u3068\u30c7\u30fc\u30bf \u30b5\u30a4\u30a8\u30f3\u30b9\u306b\u9769\u547d\u3092\u3082\u305f\u3089\u3057\u305f\u30aa\u30fc\u30d7\u30f3 \u30bd\u30fc\u30b9 \u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3067\u3059\u3002\u30e9\u30a4\u30d6 \u30b3\u30fc\u30c9\u3001\u65b9\u7a0b\u5f0f\u3001\u8996\u899a\u5316\u3001\u8aac\u660e\u6587\u3092\u542b\u3080\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3092\u4f5c\u6210\u3057\u3066\u5171\u6709\u3067\u304d\u308b Web \u30d9\u30fc\u30b9\u306e\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002\u300cJupyter\u300d\u3068\u3044\u3046\u540d\u524d\u306f\u3001Julia\u3001Python\u3001R \u3068\u3044\u3046 3 \u3064\u306e\u30b3\u30a2 \u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e\u3092\u7d44\u307f\u5408\u308f\u305b\u305f\u3082\u306e\u3067\u3001\u591a\u8a00\u8a9e\u30b5\u30dd\u30fc\u30c8\u3092\u53cd\u6620\u3057\u3066\u3044\u307e\u3059\u3002\u3053\u306e\u591a\u7528\u9014\u30c4\u30fc\u30eb\u306f\u3001\u305d\u306e\u4f7f\u3044\u3084\u3059\u3055\u3068\u5f37\u529b\u306a\u6a5f\u80fd\u306b\u3088\u308a\u3001\u30c7\u30fc\u30bf \u30b5\u30a4\u30a8\u30f3\u30c6\u30a3\u30b9\u30c8\u3001\u7814\u7a76\u8005\u3001\u6559\u80b2\u8005\u3001\u958b\u767a\u8005\u306e\u9593\u3067\u5e83\u304f\u4eba\u6c17\u3092\u535a\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n

\u6728\u661f\u306e\u8d77\u6e90\u3068\u305d\u306e\u6700\u521d\u306e\u8a00\u53ca\u306e\u6b74\u53f2<\/h2>\n

Jupyter \u306e\u8d77\u6e90\u306f\u3001\u7269\u7406\u5b66\u8005\u306e Fernando P\u00e9rez \u6c0f\u304c\u8907\u96d1\u306a\u79d1\u5b66\u8a08\u7b97\u306b\u53d6\u308a\u7d44\u3080\u969b\u306e\u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u3092\u7c21\u7d20\u5316\u3059\u308b\u305f\u3081\u306e\u30b5\u30a4\u30c9 \u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3068\u3057\u3066 IPython \u3092\u958b\u767a\u3057\u305f 2001 \u5e74\u306b\u307e\u3067\u9061\u308a\u307e\u3059\u3002IPython \u306f\u5f53\u521d\u3001Python \u306e\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6 \u30bb\u30c3\u30b7\u30e7\u30f3\u3092\u5f37\u5316\u3059\u308b\u305f\u3081\u306b\u8a2d\u8a08\u3055\u308c\u305f\u30b3\u30de\u30f3\u30c9 \u30e9\u30a4\u30f3 \u30c4\u30fc\u30eb\u3067\u3057\u305f\u3002\u6642\u9593\u304c\u7d4c\u3064\u306b\u3064\u308c\u3066\u79d1\u5b66\u754c\u3067\u4eba\u6c17\u304c\u9ad8\u307e\u308a\u30012014 \u5e74\u306b IPython \u306f\u5927\u5e45\u306a\u30d6\u30e9\u30f3\u30c9\u5909\u66f4\u3092\u7d4c\u3066 Jupyter \u306b\u9032\u5316\u3057\u307e\u3057\u305f\u3002<\/p>\n

\u4eca\u65e5\u77e5\u3089\u308c\u3066\u3044\u308b\u3088\u3046\u306b\u3001Jupyter \u304c\u521d\u3081\u3066\u8a00\u53ca\u3055\u308c\u305f\u306e\u306f 2014 \u5e74\u3001\u30da\u30ec\u30b9\u3068\u30d6\u30e9\u30a4\u30a2\u30f3\u30fb\u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u304c IPython \u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306e\u4e00\u74b0\u3068\u3057\u3066\u305d\u308c\u3092\u5c0e\u5165\u3057\u305f\u3068\u304d\u3067\u3057\u305f\u3002\u3053\u306e 2 \u4eba\u306e\u30d3\u30b8\u30e7\u30f3\u306f\u3001\u8907\u6570\u306e\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e\u3092\u30b5\u30dd\u30fc\u30c8\u3059\u308b\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0 \u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3092\u4f5c\u6210\u3057\u3001\u79d1\u5b66\u8005\u3084\u7814\u7a76\u8005\u304c\u5171\u540c\u4f5c\u696d\u3092\u884c\u3044\u3001\u7814\u7a76\u7d50\u679c\u3092\u52b9\u679c\u7684\u306b\u5171\u6709\u3057\u3084\u3059\u304f\u3059\u308b\u3053\u3068\u3067\u3057\u305f\u3002<\/p>\n

Jupyter\u306e\u8a73\u7d30\u60c5\u5831: Jupyter\u306e\u30c8\u30d4\u30c3\u30af\u306e\u62e1\u5f35<\/h2>\n

Jupyter \u306f\u3001\u30e9\u30a4\u30d6 \u30b3\u30fc\u30c9\u3001\u30c6\u30ad\u30b9\u30c8\u306e\u8aac\u660e\u3001\u65b9\u7a0b\u5f0f\u3001\u8996\u899a\u5316\u3092\u542b\u3080\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u3042\u308b\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u6982\u5ff5\u306b\u57fa\u3065\u3044\u3066\u52d5\u4f5c\u3057\u307e\u3059\u3002\u3053\u308c\u3089\u306e\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306b\u3088\u308a\u3001\u30c7\u30fc\u30bf \u30b5\u30a4\u30a8\u30f3\u30c6\u30a3\u30b9\u30c8\u3084\u7814\u7a76\u8005\u306f\u30c7\u30fc\u30bf\u5206\u6790\u3092\u5b9f\u884c\u3057\u3001\u5b9f\u9a13\u3092\u30b7\u30df\u30e5\u30ec\u30fc\u30c8\u3057\u3001\u4ed6\u306e\u30e6\u30fc\u30b6\u30fc\u3068\u30b7\u30fc\u30e0\u30ec\u30b9\u306b\u4f5c\u696d\u3092\u5171\u6709\u3067\u304d\u307e\u3059\u3002Jupyter \u306e\u4e3b\u8981\u30b3\u30f3\u30dd\u30fc\u30cd\u30f3\u30c8\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/p>\n

    \n
  1. \n

    \u30ab\u30fc\u30cd\u30eb<\/strong>: \u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u5185\u306e\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3057\u3001\u7d50\u679c\u3092\u30e6\u30fc\u30b6\u30fc \u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9\u306b\u8fd4\u3059\u8a08\u7b97\u30a8\u30f3\u30b8\u30f3\u3002<\/p>\n<\/li>\n

  2. \n

    \u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30fc\u30b9<\/strong>: \u30e6\u30fc\u30b6\u30fc\u304c\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u4f5c\u6210\u3001\u7de8\u96c6\u3001\u5b9f\u884c\u3067\u304d\u308b\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u74b0\u5883\u3092\u63d0\u4f9b\u3059\u308b Web \u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u3002<\/p>\n<\/li>\n

  3. \n

    \u7d30\u80de<\/strong>: Jupyter \u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u57fa\u672c\u5358\u4f4d\u3067\u3001\u30b3\u30fc\u30c9\u307e\u305f\u306f Markdown \u30c6\u30ad\u30b9\u30c8\u304c\u542b\u307e\u308c\u307e\u3059\u3002\u30e6\u30fc\u30b6\u30fc\u306f\u30b3\u30fc\u30c9 \u30bb\u30eb\u3092\u500b\u5225\u306b\u5b9f\u884c\u3067\u304d\u308b\u305f\u3081\u3001\u5206\u6790\u306e\u3055\u307e\u3056\u307e\u306a\u90e8\u5206\u3092\u7c21\u5358\u306b\u8a66\u3059\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<\/li>\n

  4. \n

    \u30de\u30fc\u30af\u30c0\u30a6\u30f3<\/strong>: \u30e6\u30fc\u30b6\u30fc\u304c\u30c6\u30ad\u30b9\u30c8\u3092\u30d5\u30a9\u30fc\u30de\u30c3\u30c8\u3057\u305f\u308a\u3001\u898b\u51fa\u3057\u3001\u30ea\u30b9\u30c8\u3001\u8868\u3092\u4f5c\u6210\u3057\u305f\u308a\u3001\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u5185\u306b\u30de\u30eb\u30c1\u30e1\u30c7\u30a3\u30a2\u8981\u7d20\u3092\u7d44\u307f\u8fbc\u3093\u3060\u308a\u3067\u304d\u308b\u8efd\u91cf\u30de\u30fc\u30af\u30a2\u30c3\u30d7\u8a00\u8a9e\u3067\u3059\u3002<\/p>\n<\/li>\n

  5. \n

    \u30b3\u30fc\u30c9\u306e\u5b9f\u884c<\/strong>Jupyter \u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u3067\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3067\u304d\u308b\u305f\u3081\u3001\u7d50\u679c\u306b\u95a2\u3059\u308b\u30d5\u30a3\u30fc\u30c9\u30d0\u30c3\u30af\u304c\u5373\u5ea7\u306b\u5f97\u3089\u308c\u3001\u53cd\u5fa9\u7684\u306a\u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u304c\u5bb9\u6613\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n<\/li>\n

  6. \n

    \u8996\u899a\u5316<\/strong>Jupyter \u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306f\u3001Matplotlib \u3084 Seaborn \u306a\u3069\u306e\u3055\u307e\u3056\u307e\u306a\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u304a\u308a\u3001\u30e6\u30fc\u30b6\u30fc\u306f\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u5185\u3067\u76f4\u63a5\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u30c1\u30e3\u30fc\u30c8\u3084\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002<\/p>\n<\/li>\n<\/ol>\n

    Jupyter\u306e\u5185\u90e8\u69cb\u9020: Jupyter\u306e\u4ed5\u7d44\u307f<\/h2>\n

    Jupyter \u306e\u5185\u90e8\u52d5\u4f5c\u3092\u7406\u89e3\u3059\u308b\u305f\u3081\u306b\u3001\u305d\u306e\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u898b\u3066\u307f\u307e\u3057\u3087\u3046\u3002\u30e6\u30fc\u30b6\u30fc\u304c Jupyter \u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u958b\u304f\u3068\u3001\u6b21\u306e\u624b\u9806\u304c\u5b9f\u884c\u3055\u308c\u307e\u3059\u3002<\/p>\n

      \n
    1. \n

      Jupyter \u30b5\u30fc\u30d0\u30fc\u304c\u8d77\u52d5\u3057\u3001\u30e6\u30fc\u30b6\u30fc\u306e Web \u30d6\u30e9\u30a6\u30b6\u30fc\u304b\u3089\u306e\u7740\u4fe1\u63a5\u7d9a\u3092\u30ea\u30c3\u30b9\u30f3\u3057\u307e\u3059\u3002<\/p>\n<\/li>\n

    2. \n

      \u30ce\u30fc\u30c8\u30d6\u30c3\u30af \u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9\u306f\u30e6\u30fc\u30b6\u30fc\u306e\u30d6\u30e9\u30a6\u30b6\u30fc\u306b\u30ec\u30f3\u30c0\u30ea\u30f3\u30b0\u3055\u308c\u3001\u30bb\u30eb\u306e\u4f5c\u6210\u3001\u5909\u66f4\u3001\u5b9f\u884c\u304c\u53ef\u80fd\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n<\/li>\n

    3. \n

      \u30e6\u30fc\u30b6\u30fc\u304c\u30b3\u30fc\u30c9 \u30bb\u30eb\u3092\u5b9f\u884c\u3059\u308b\u3068\u3001\u30b3\u30fc\u30c9\u306f Jupyter \u30b5\u30fc\u30d0\u30fc\u306b\u9001\u4fe1\u3055\u308c\u3001\u9069\u5207\u306a\u30ab\u30fc\u30cd\u30eb\u306b\u8ee2\u9001\u3055\u308c\u307e\u3059\u3002<\/p>\n<\/li>\n

    4. \n

      \u30ab\u30fc\u30cd\u30eb\u306f\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3057\u3001\u51fa\u529b\u3092 Jupyter \u30b5\u30fc\u30d0\u30fc\u306b\u8fd4\u3057\u307e\u3059\u3002<\/p>\n<\/li>\n

    5. \n

      Jupyter \u30b5\u30fc\u30d0\u30fc\u306f\u51fa\u529b\u3092\u30e6\u30fc\u30b6\u30fc\u306e\u30d6\u30e9\u30a6\u30b6\u306b\u9001\u308a\u8fd4\u3057\u3001\u30b3\u30fc\u30c9 \u30bb\u30eb\u306e\u4e0b\u306b\u8868\u793a\u3055\u308c\u307e\u3059\u3002<\/p>\n<\/li>\n

    6. \n

      Markdown \u30bb\u30eb\u306f\u3001\u30ce\u30fc\u30c8\u30d6\u30c3\u30af \u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9\u3067\u76f4\u63a5\u3001\u66f8\u5f0f\u8a2d\u5b9a\u3055\u308c\u305f\u30c6\u30ad\u30b9\u30c8\u3068\u3057\u3066\u30ec\u30f3\u30c0\u30ea\u30f3\u30b0\u3055\u308c\u307e\u3059\u3002<\/p>\n<\/li>\n<\/ol>\n

      \u3053\u306e\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3\u306b\u3088\u308a\u3001\u30e6\u30fc\u30b6\u30fc \u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9 (\u30ce\u30fc\u30c8\u30d6\u30c3\u30af \u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9) \u3092\u8a08\u7b97\u30a8\u30f3\u30b8\u30f3 (\u30ab\u30fc\u30cd\u30eb) \u304b\u3089\u5206\u96e2\u3067\u304d\u308b\u305f\u3081\u3001\u30e6\u30fc\u30b6\u30fc\u306f\u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9\u3092\u5909\u66f4\u305b\u305a\u306b\u7570\u306a\u308b\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e\u3092\u5207\u308a\u66ff\u3048\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n

      Jupyter\u306e\u4e3b\u8981\u6a5f\u80fd\u306e\u5206\u6790<\/h2>\n

      Jupyter \u306e\u4e3b\u306a\u6a5f\u80fd\u306b\u3088\u308a\u3001\u30c7\u30fc\u30bf \u30b5\u30a4\u30a8\u30f3\u30c6\u30a3\u30b9\u30c8\u3001\u7814\u7a76\u8005\u3001\u6559\u80b2\u8005\u306b\u3068\u3063\u3066\u4e0d\u53ef\u6b20\u306a\u30c4\u30fc\u30eb\u3068\u306a\u3063\u3066\u3044\u307e\u3059\u3002\u6ce8\u76ee\u3059\u3079\u304d\u6a5f\u80fd\u306b\u306f\u6b21\u306e\u3088\u3046\u306a\u3082\u306e\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n

        \n
      1. \n

        \u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u6027<\/strong>Jupyter \u306f\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u74b0\u5883\u3092\u63d0\u4f9b\u3057\u3001\u30e6\u30fc\u30b6\u30fc\u304c\u30b3\u30fc\u30c9 \u30bb\u30eb\u3092\u5909\u66f4\u304a\u3088\u3073\u5b9f\u884c\u3067\u304d\u308b\u3088\u3046\u306b\u3059\u308b\u305f\u3081\u3001\u30c7\u30fc\u30bf\u306e\u63a2\u7d22\u3068\u5b9f\u9a13\u306b\u6700\u9069\u3067\u3059\u3002<\/p>\n<\/li>\n

      2. \n

        \u30c7\u30fc\u30bf\u306e\u8996\u899a\u5316<\/strong>Jupyter \u306f\u3055\u307e\u3056\u307e\u306a\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u304a\u308a\u3001\u30e6\u30fc\u30b6\u30fc\u306f\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u5185\u3067\u76f4\u63a5\u3001\u9b45\u529b\u7684\u3067\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u8996\u899a\u5316\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002<\/p>\n<\/li>\n

      3. \n

        \u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3<\/strong>: Jupyter \u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306f\u4ed6\u306e\u30e6\u30fc\u30b6\u30fc\u3068\u5171\u6709\u3067\u304d\u308b\u305f\u3081\u3001\u30c1\u30fc\u30e0 \u30e1\u30f3\u30d0\u30fc\u3084\u7814\u7a76\u8005\u9593\u306e\u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u4fc3\u9032\u3067\u304d\u307e\u3059\u3002<\/p>\n<\/li>\n

      4. \n

        \u30c9\u30ad\u30e5\u30e1\u30f3\u30c6\u30fc\u30b7\u30e7\u30f3<\/strong>: Jupyter \u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u5185\u306e\u30b3\u30fc\u30c9\u3068 Markdown \u30c6\u30ad\u30b9\u30c8\u306e\u7d44\u307f\u5408\u308f\u305b\u306b\u3088\u308a\u3001\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u3067\u6709\u76ca\u306a\u30c7\u30fc\u30bf\u5206\u6790\u30ec\u30dd\u30fc\u30c8\u3092\u4f5c\u6210\u3059\u308b\u305f\u3081\u306e\u512a\u308c\u305f\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u304c\u5b9f\u73fe\u3057\u307e\u3059\u3002<\/p>\n<\/li>\n

      5. \n

        \u4e26\u5217\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0<\/strong>Jupyter \u306f\u4e26\u5217\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u304a\u308a\u3001\u30e6\u30fc\u30b6\u30fc\u306f\u8a08\u7b97\u96c6\u7d04\u578b\u306e\u30bf\u30b9\u30af\u306b\u8907\u6570\u306e\u30b3\u30a2\u307e\u305f\u306f\u30af\u30e9\u30b9\u30bf\u30fc\u3092\u6d3b\u7528\u3067\u304d\u307e\u3059\u3002<\/p>\n<\/li>\n

      6. \n

        \u6559\u80b2<\/strong>Jupyter \u306f\u6559\u80b2\u73fe\u5834\u3067\u5e83\u304f\u4f7f\u7528\u3055\u308c\u3066\u304a\u308a\u3001\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u5b66\u7fd2\u4f53\u9a13\u3084\u5b9f\u8df5\u7684\u306a\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u6f14\u7fd2\u3092\u4fc3\u9032\u3057\u307e\u3059\u3002<\/p>\n<\/li>\n<\/ol>\n

        Jupyter\u306e\u7a2e\u985e: \u30c6\u30fc\u30d6\u30eb\u3068\u30ea\u30b9\u30c8\u3092\u4f7f\u7528\u3057\u3066\u8a18\u8ff0\u3059\u308b<\/h2>\n

        Jupyter \u306f\u3001\u591a\u69d8\u306a\u30ab\u30fc\u30cd\u30eb \u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u3092\u901a\u3058\u3066\u3055\u307e\u3056\u307e\u306a\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u3002\u6b21\u306e\u8868\u306f\u3001\u5229\u7528\u53ef\u80fd\u306a\u4e00\u822c\u7684\u306a\u30ab\u30fc\u30cd\u30eb\u306e\u4e00\u90e8\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n\n\n\n\n\n\n\n\n
        \u30ab\u30fc\u30cd\u30eb<\/th>\n\u30b5\u30dd\u30fc\u30c8\u3055\u308c\u3066\u3044\u308b\u8a00\u8a9e<\/th>\n<\/tr>\n<\/thead>\n
        Python \u306e<\/td>\nPython\u3001Julia\u3001R\u306a\u3069<\/td>\n<\/tr>\n
        IR\u30ab\u30fc\u30cd\u30eb<\/td>\nR<\/td>\n<\/tr>\n
        \u30b8\u30e5\u30ea\u30a2<\/td>\n\u30b8\u30e5\u30ea\u30a2<\/td>\n<\/tr>\n
        \u30cf\u30b9\u30b1\u30eb<\/td>\n\u30cf\u30b9\u30b1\u30eb<\/td>\n<\/tr>\n
        \u30a4\u30de\u30c8\u30e9\u30dc<\/td>\n\u30de\u30c6\u30ea\u30a2\u30e9\u30a4\u30ba\u30c9<\/td>\n<\/tr>\n
        \u30eb\u30d3\u30fc<\/td>\n\u30eb\u30d3\u30fc<\/td>\n<\/tr>\n
        \u30b9\u30ab\u30e9<\/td>\n\u30b9\u30ab\u30e9<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        \u3053\u308c\u3089\u306e\u6a19\u6e96\u30ab\u30fc\u30cd\u30eb\u4ee5\u5916\u306b\u3082\u3001Lua\u3001C++\u3001Go \u306a\u3069\u306e\u8a00\u8a9e\u5411\u3051\u306e\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u4e3b\u5c0e\u306e\u30ab\u30fc\u30cd\u30eb\u3082\u898b\u3064\u304b\u308a\u3001Jupyter \u306e\u6c4e\u7528\u6027\u304c\u62e1\u5f35\u3055\u308c\u3001\u3055\u307e\u3056\u307e\u306a\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0 \u30cb\u30fc\u30ba\u306b\u5bfe\u5fdc\u3067\u304d\u307e\u3059\u3002<\/p>\n

        Jupyter\u306e\u4f7f\u3044\u65b9\u3001\u4f7f\u7528\u4e0a\u306e\u554f\u984c\u3068\u305d\u306e\u89e3\u6c7a\u7b56<\/h2>\n

        Jupyter \u306f\u3001\u6b21\u306e\u3088\u3046\u306a\u5e45\u5e83\u3044\u30e6\u30fc\u30b9\u30b1\u30fc\u30b9\u3067\u5fdc\u7528\u3055\u308c\u3066\u3044\u307e\u3059\u3002<\/p>\n

          \n
        1. \n

          \u30c7\u30fc\u30bf\u5206\u6790\u3068\u8996\u899a\u5316<\/strong>\u30c7\u30fc\u30bf \u30b5\u30a4\u30a8\u30f3\u30c6\u30a3\u30b9\u30c8\u306f\u3001Jupyter \u3092\u6d3b\u7528\u3057\u3066\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u63a2\u7d22\u3057\u3001\u8996\u899a\u5316\u3092\u4f5c\u6210\u3057\u3001\u7d71\u8a08\u5206\u6790\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/p>\n<\/li>\n

        2. \n

          \u6a5f\u68b0\u5b66\u7fd2<\/strong>Jupyter \u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306f\u3001\u6a5f\u68b0\u5b66\u7fd2\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306b\u304a\u3051\u308b\u30e2\u30c7\u30eb\u306e\u958b\u767a\u3001\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3001\u8a55\u4fa1\u3092\u5bb9\u6613\u306b\u3057\u307e\u3059\u3002<\/p>\n<\/li>\n

        3. \n

          \u79d1\u5b66\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0<\/strong>\u7814\u7a76\u8005\u3084\u79d1\u5b66\u8005\u306f\u3001\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u3001\u8a08\u7b97\u30e2\u30c7\u30ea\u30f3\u30b0\u3001\u5b9f\u9a13\u30c7\u30fc\u30bf\u306e\u5206\u6790\u306b Jupyter \u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/p>\n<\/li>\n

        4. \n

          \u6559\u3048\u308b\u3053\u3068\u3068\u5b66\u3076\u3053\u3068<\/strong>Jupyter \u306f\u3001\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u3001\u30c7\u30fc\u30bf \u30b5\u30a4\u30a8\u30f3\u30b9\u3001\u305d\u306e\u4ed6\u306e\u79d1\u5b66\u5206\u91ce\u3092\u6559\u3048\u308b\u305f\u3081\u306e\u5f37\u529b\u306a\u6559\u80b2\u30c4\u30fc\u30eb\u3068\u3057\u3066\u6a5f\u80fd\u3057\u307e\u3059\u3002<\/p>\n<\/li>\n<\/ol>\n

          \u305f\u3060\u3057\u3001\u4ed6\u306e\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u3068\u540c\u69d8\u306b\u3001Jupyter \u306e\u4f7f\u7528\u4e2d\u306b\u30e6\u30fc\u30b6\u30fc\u304c\u3044\u304f\u3064\u304b\u306e\u8ab2\u984c\u306b\u906d\u9047\u3059\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002\u4e00\u822c\u7684\u306a\u554f\u984c\u3068\u305d\u306e\u89e3\u6c7a\u7b56\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/p>\n

            \n
          1. \n

            \u30e1\u30e2\u30ea\u4f7f\u7528\u91cf<\/strong>: \u5927\u898f\u6a21\u306a\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3084\u30e1\u30e2\u30ea\u3092\u5927\u91cf\u306b\u6d88\u8cbb\u3059\u308b\u64cd\u4f5c\u306f\u3001\u904e\u5270\u306a\u30e1\u30e2\u30ea\u6d88\u8cbb\u306b\u3064\u306a\u304c\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002\u30e6\u30fc\u30b6\u30fc\u306f\u3001\u30b3\u30fc\u30c9\u3092\u6700\u9069\u5316\u3059\u308b\u304b\u3001\u30af\u30e9\u30a6\u30c9 \u30ea\u30bd\u30fc\u30b9\u3092\u4f7f\u7528\u3057\u3066\u30e1\u30e2\u30ea\u3092\u5897\u3084\u3059\u3053\u3068\u3092\u691c\u8a0e\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n<\/li>\n

          2. \n

            \u30ab\u30fc\u30cd\u30eb\u30af\u30e9\u30c3\u30b7\u30e5<\/strong>: \u5834\u5408\u306b\u3088\u3063\u3066\u306f\u3001\u30b3\u30fc\u30c9\u306e\u554f\u984c\u306b\u3088\u308a\u30ab\u30fc\u30cd\u30eb\u304c\u30af\u30e9\u30c3\u30b7\u30e5\u3059\u308b\u3053\u3068\u304c\u3042\u308a\u307e\u3059\u3002\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u5b9a\u671f\u7684\u306b\u4fdd\u5b58\u3059\u308b\u3068\u3001\u305d\u306e\u3088\u3046\u306a\u72b6\u6cc1\u3067\u3082\u4f5c\u696d\u3092\u56de\u5fa9\u3057\u3084\u3059\u304f\u306a\u308a\u307e\u3059\u3002<\/p>\n<\/li>\n

          3. \n

            \u30d0\u30fc\u30b8\u30e7\u30f3\u306e\u7af6\u5408<\/strong>: \u30e9\u30a4\u30d6\u30e9\u30ea\u9593\u306e\u4f9d\u5b58\u95a2\u4fc2\u306e\u554f\u984c\u306b\u3088\u308a\u7af6\u5408\u304c\u767a\u751f\u3059\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002\u4eee\u60f3\u74b0\u5883\u3084\u30b3\u30f3\u30c6\u30ca\u5316\u3092\u5229\u7528\u3059\u308b\u3068\u3001\u3053\u308c\u3089\u306e\u554f\u984c\u3092\u8efd\u6e1b\u3067\u304d\u307e\u3059\u3002<\/p>\n<\/li>\n

          4. \n

            \u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u4e0a\u306e\u61f8\u5ff5<\/strong>: \u9069\u5207\u306a\u30b5\u30cb\u30bf\u30a4\u30ba\u3092\u884c\u308f\u305a\u306b\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3092\u5171\u6709\u3059\u308b\u3068\u3001\u6f5c\u5728\u7684\u306a\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3 \u30ea\u30b9\u30af\u306b\u3064\u306a\u304c\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002\u6a5f\u5bc6\u30c7\u30fc\u30bf\u306e\u516c\u958b\u3084\u4fe1\u983c\u3067\u304d\u306a\u3044\u30b3\u30fc\u30c9\u306e\u4f7f\u7528\u3092\u907f\u3051\u308b\u3053\u3068\u304c\u91cd\u8981\u3067\u3059\u3002<\/p>\n<\/li>\n<\/ol>\n

            \u4e3b\u306a\u7279\u5fb4\u3068\u305d\u306e\u4ed6\u306e\u985e\u4f3c\u7528\u8a9e\u3068\u306e\u6bd4\u8f03\u3092\u8868\u3068\u30ea\u30b9\u30c8\u306e\u5f62\u5f0f\u3067\u793a\u3057\u307e\u3059\u3002<\/h2>\n

            Jupyter \u3092\u540c\u69d8\u306e\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6 \u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0 \u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3068\u6bd4\u8f03\u3057\u3066\u3001\u305d\u306e\u4e3b\u306a\u7279\u5fb4\u3092\u660e\u3089\u304b\u306b\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n\n\n\n\n\n\n\n\n\n
            \u7279\u5fb4<\/th>\n\u30b8\u30e5\u30d4\u30bf\u30fc<\/th>\nRStudio<\/th>\nGoogle \u30b3\u30e9\u30dc<\/th>\n<\/tr>\n<\/thead>\n
            \u591a\u8a00\u8a9e\u30b5\u30dd\u30fc\u30c8<\/td>\n\u306f\u3044\uff08\u30ab\u30fc\u30cd\u30eb\u7d4c\u7531\uff09<\/td>\n\u9650\u5b9a\u7248\uff08\u4e3b\u306bR\uff09<\/td>\n\u30d1\u30a4\u30bd\u30f3<\/td>\n<\/tr>\n
            \u30af\u30e9\u30a6\u30c9\u30d9\u30fc\u30b9\u306e\u5b9f\u884c<\/td>\n\u53ef\u80fd<\/td>\n\u3044\u3044\u3048<\/td>\n\u306f\u3044<\/td>\n<\/tr>\n
            \u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3<\/td>\n\u306f\u3044<\/td>\n\u9650\u5b9a<\/td>\n\u306f\u3044<\/td>\n<\/tr>\n
            \u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea<\/td>\n\u5e83\u7bc4\u306a\u30b5\u30dd\u30fc\u30c8<\/td>\n\u9650\u5b9a<\/td>\n\u306f\u3044<\/td>\n<\/tr>\n
            \u5b66\u7fd2\u66f2\u7dda<\/td>\n\u9069\u5ea6<\/td>\n\u4f4e\u3044<\/td>\n\u4f4e\u3044<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

            Jupyter \u306f\u3001\u591a\u8a00\u8a9e\u30b5\u30dd\u30fc\u30c8\u3001\u30af\u30e9\u30a6\u30c9\u30d9\u30fc\u30b9\u306e\u5b9f\u884c\u3001\u5e83\u7bc4\u306a\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u969b\u7acb\u3063\u3066\u3044\u307e\u3059\u3002\u4e00\u65b9\u3001RStudio \u306f R \u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u5c02\u7528\u306e\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3068\u3057\u3066\u512a\u308c\u3066\u304a\u308a\u3001Google Colab \u306f\u4f7f\u3044\u3084\u3059\u3055\u3068 Google Drive \u3068\u306e\u76f4\u63a5\u7d71\u5408\u3067\u4eba\u6c17\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n

            Jupyter\u306b\u95a2\u9023\u3059\u308b\u5c06\u6765\u306e\u5c55\u671b\u3068\u6280\u8853<\/h2>\n

            Jupyter \u306e\u5c06\u6765\u306f\u6709\u671b\u306b\u898b\u3048\u3001\u3044\u304f\u3064\u304b\u306e\u958b\u767a\u304c\u4e88\u5b9a\u3055\u308c\u3066\u3044\u307e\u3059\u3002<\/p>\n

              \n
            1. \n

              AI\u3068ML\u306e\u7d71\u5408<\/strong>Jupyter \u306f AI \u3084\u6a5f\u68b0\u5b66\u7fd2\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u3068\u306e\u3055\u3089\u306a\u308b\u7d71\u5408\u304c\u898b\u8fbc\u307e\u308c\u3001\u9ad8\u5ea6\u306a\u30e2\u30c7\u30eb\u306e\u958b\u767a\u3068\u5c55\u958b\u304c\u52b9\u7387\u5316\u3055\u308c\u308b\u3067\u3057\u3087\u3046\u3002<\/p>\n<\/li>\n

            2. \n

              \u5f37\u5316\u3055\u308c\u305f\u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3<\/strong>: \u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3\u6a5f\u80fd\u3092\u5f37\u5316\u3059\u308b\u53d6\u308a\u7d44\u307f\u306b\u3088\u308a\u3001\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u4e0a\u3067\u306e\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u306e\u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3\u304c\u53ef\u80fd\u306b\u306a\u308a\u3001\u30ea\u30e2\u30fc\u30c8\u3067\u306e\u30c1\u30fc\u30e0\u30ef\u30fc\u30af\u304c\u3088\u308a\u52b9\u7387\u7684\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n<\/li>\n

            3. \n

              \u30af\u30e9\u30a6\u30c9\u30d9\u30fc\u30b9\u306e\u9032\u6b69<\/strong>\u30af\u30e9\u30a6\u30c9\u30d9\u30fc\u30b9\u306e Jupyter \u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306f\u3001\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u3001\u30b9\u30b1\u30fc\u30e9\u30d3\u30ea\u30c6\u30a3\u3001\u30a2\u30af\u30bb\u30b7\u30d3\u30ea\u30c6\u30a3\u304c\u5411\u4e0a\u3059\u308b\u53ef\u80fd\u6027\u304c\u9ad8\u304f\u3001\u30c7\u30fc\u30bf\u96c6\u7d04\u578b\u306e\u30bf\u30b9\u30af\u306b\u3068\u3063\u3066\u3088\u308a\u9b45\u529b\u7684\u306a\u3082\u306e\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n<\/li>\n

            4. \n

              \u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u30c7\u30fc\u30bf\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3<\/strong>Jupyter \u306e\u9032\u5316\u306b\u3088\u308a\u3001\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u30c7\u30fc\u30bf \u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u304c\u751f\u307e\u308c\u3001\u30e6\u30fc\u30b6\u30fc\u306f\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u30c7\u30fc\u30bf\u99c6\u52d5\u578b Web \u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u3092\u69cb\u7bc9\u3057\u3066\u5171\u6709\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n<\/li>\n<\/ol>\n

              \u30d7\u30ed\u30ad\u30b7\u30b5\u30fc\u30d0\u30fc\u3092Jupyter\u3067\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3084Jupyter\u3068\u95a2\u9023\u4ed8\u3051\u308b\u65b9\u6cd5<\/h2>\n

              OneProxy \u304c\u63d0\u4f9b\u3059\u308b\u3088\u3046\u306a\u30d7\u30ed\u30ad\u30b7 \u30b5\u30fc\u30d0\u30fc\u306f\u3001Jupyter \u30a8\u30af\u30b9\u30da\u30ea\u30a8\u30f3\u30b9\u306e\u5411\u4e0a\u306b\u91cd\u8981\u306a\u5f79\u5272\u3092\u679c\u305f\u3057\u307e\u3059\u3002\u30d7\u30ed\u30ad\u30b7 \u30b5\u30fc\u30d0\u30fc\u3092 Jupyter \u3067\u4f7f\u7528\u3057\u305f\u308a\u95a2\u9023\u4ed8\u3051\u305f\u308a\u3059\u308b\u65b9\u6cd5\u306f\u3001\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/p>\n

                \n
              1. \n

                \u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u306e\u5f37\u5316<\/strong>: \u30d7\u30ed\u30ad\u30b7 \u30b5\u30fc\u30d0\u30fc\u306f\u3001\u30e6\u30fc\u30b6\u30fc\u3068 Jupyter \u30b5\u30fc\u30d0\u30fc\u9593\u306e\u4ef2\u4ecb\u5f79\u3068\u3057\u3066\u6a5f\u80fd\u3057\u3001\u30e6\u30fc\u30b6\u30fc\u306e IP \u30a2\u30c9\u30ec\u30b9\u3092\u96a0\u3057\u3001\u6f5c\u5728\u7684\u306a\u30b5\u30a4\u30d0\u30fc\u8105\u5a01\u3092\u8efd\u6e1b\u3059\u308b\u3053\u3068\u3067\u3001\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u3092\u3055\u3089\u306b\u5f37\u5316\u3057\u307e\u3059\u3002<\/p>\n<\/li>\n

              2. \n

                \u5236\u9650\u306e\u56de\u907f<\/strong>: \u7279\u5b9a\u306e\u5730\u57df\u3084\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3067\u306f\u3001Jupyter \u307e\u305f\u306f\u7279\u5b9a\u306e\u30ab\u30fc\u30cd\u30eb\u3078\u306e\u30a2\u30af\u30bb\u30b9\u304c\u5236\u9650\u3055\u308c\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002\u30d7\u30ed\u30ad\u30b7 \u30b5\u30fc\u30d0\u30fc\u306f\u3001\u30e6\u30fc\u30b6\u30fc\u304c\u3053\u308c\u3089\u306e\u5236\u9650\u3092\u56de\u907f\u3057\u3001\u30b7\u30fc\u30e0\u30ec\u30b9\u306b Jupyter \u306b\u30a2\u30af\u30bb\u30b9\u3059\u308b\u306e\u306b\u5f79\u7acb\u3061\u307e\u3059\u3002<\/p>\n<\/li>\n

              3. \n

                \u533f\u540d\u6027\u3068\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc<\/strong>: \u30d7\u30ed\u30ad\u30b7 \u30b5\u30fc\u30d0\u30fc\u306f\u3001\u30e6\u30fc\u30b6\u30fc\u306e\u533f\u540d\u6027\u3068\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u3092\u5f37\u5316\u3057\u3001\u30e6\u30fc\u30b6\u30fc\u304c\u81ea\u5206\u306e\u672c\u5f53\u306e\u8eab\u5143\u3092\u660e\u304b\u3055\u305a\u306b Jupyter \u3092\u4f7f\u7528\u3067\u304d\u308b\u3088\u3046\u306b\u3057\u307e\u3059\u3002<\/p>\n<\/li>\n

              4. \n

                \u30ed\u30fc\u30c9\u30d0\u30e9\u30f3\u30b7\u30f3\u30b0<\/strong>: \u8907\u6570\u306e Jupyter \u30b5\u30fc\u30d0\u30fc\u304c\u5c55\u958b\u3055\u308c\u3066\u3044\u308b\u30b7\u30ca\u30ea\u30aa\u3067\u306f\u3001\u30d7\u30ed\u30ad\u30b7 \u30b5\u30fc\u30d0\u30fc\u306f\u7740\u4fe1\u30c8\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u52b9\u7387\u7684\u306b\u5206\u6563\u3057\u3001\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u3068\u30ea\u30bd\u30fc\u30b9\u4f7f\u7528\u7387\u3092\u6700\u9069\u5316\u3067\u304d\u307e\u3059\u3002<\/p>\n<\/li>\n<\/ol>\n

                \u30d7\u30ed\u30ad\u30b7 \u30b5\u30fc\u30d0\u30fc\u3092\u6d3b\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u30e6\u30fc\u30b6\u30fc\u306f Jupyter \u30a8\u30af\u30b9\u30da\u30ea\u30a8\u30f3\u30b9\u3092\u5f37\u5316\u3057\u3001\u5730\u7406\u7684\u5236\u9650\u3084\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u4e0a\u306e\u61f8\u5ff5\u306b\u3088\u3063\u3066\u8ab2\u3055\u308c\u308b\u6f5c\u5728\u7684\u306a\u5236\u9650\u3092\u514b\u670d\u3067\u304d\u307e\u3059\u3002<\/p>\n

                \u95a2\u9023\u30ea\u30f3\u30af<\/h2>\n

                Jupyter \u306e\u8a73\u7d30\u306b\u3064\u3044\u3066\u306f\u3001\u6b21\u306e\u30ea\u30bd\u30fc\u30b9\u3092\u53c2\u7167\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n

                  \n
                1. Jupyter \u516c\u5f0f\u30b5\u30a4\u30c8<\/a><\/li>\n
                2. Jupyter \u30c9\u30ad\u30e5\u30e1\u30f3\u30c8<\/a><\/li>\n
                3. Jupyter GitHub \u30ea\u30dd\u30b8\u30c8\u30ea<\/a><\/li>\n
                4. Jupyter Notebook \u306e\u4f8b<\/a><\/li>\n<\/ol>","protected":false},"featured_media":468719,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-477756","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about Jupyter: Empowering Data Science and Interactive Computing<\/mark>","faq_items":[{"question":"What is Jupyter?","answer":"

                  Jupyter is an open-source project that provides a web-based platform for interactive computing and data science. It allows users to create documents containing live code, visualizations, equations, and text explanations.<\/p>"},{"question":"How did Jupyter originate, and when was it first mentioned?","answer":"

                  Jupyter originated as IPython in 2001 when physicist Fernando P\u00e9rez developed it to streamline his scientific computations. In 2014, IPython was rebranded as Jupyter, with its first mention as part of the IPython project.<\/p>"},{"question":"What is the internal structure of Jupyter, and how does it work?","answer":"

                  Jupyter consists of a kernel, notebook interface, code cells, Markdown cells, and visualization capabilities. When a user runs a code cell, the code is executed by the kernel, and the output is sent back to the notebook interface.<\/p>"},{"question":"What are the key features of Jupyter?","answer":"

                  Jupyter's key features include interactivity, data visualization support, collaboration options, extensive documentation capabilities, and the ability to perform parallel computing tasks.<\/p>"},{"question":"What types of Jupyter exist?","answer":"

                  Jupyter supports various programming languages through its kernels. Some popular kernels include IPython (Python, Julia, R, and more), IRkernel (R), IJulia (Julia), IHaskell (Haskell), IMATLAB (MATLAB), IRuby (Ruby), and IScala (Scala).<\/p>"},{"question":"How can Jupyter be used, and what are the common problems and solutions related to its use?","answer":"

                  Jupyter finds applications in data analysis, machine learning, scientific computing, and education. Common problems include memory usage, kernel crashes, version conflicts, and security concerns, which can be addressed through optimization, regular saving, virtual environments, and careful sharing.<\/p>"},{"question":"How does Jupyter compare to similar platforms like RStudio and Google Colab?","answer":"

                  Jupyter stands out for its multi-language support, cloud-based execution, and extensive visualization libraries. RStudio excels as a dedicated platform for R programming, while Google Colab is known for its simplicity and direct integration with Google Drive.<\/p>"},{"question":"What are the future perspectives and technologies related to Jupyter?","answer":"

                  The future of Jupyter holds possibilities for integration with AI and machine learning, improved collaboration features, advancements in cloud-based execution, and the development of interactive data applications.<\/p>"},{"question":"How can proxy servers be associated with Jupyter?","answer":"

                  Proxy servers, like those provided by OneProxy, can enhance Jupyter's security, bypass restrictions, provide anonymity, and enable load balancing for optimal performance.<\/p>"},{"question":"Where can I find more information about Jupyter?","answer":"

                  For more information about Jupyter, visit the official website, explore the documentation, check out the GitHub repository, and find useful Jupyter notebook examples.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/jp\/wp-json\/wp\/v2\/wiki\/477756","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/jp\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/jp\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/jp\/wp-json\/wp\/v2\/wiki\/477756\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/jp\/wp-json\/wp\/v2\/media\/468719"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/jp\/wp-json\/wp\/v2\/media?parent=477756"}],"curies":[{"name":"\u3046\u30fc\u3093","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}