{"id":1113,"date":"2023-07-27T15:00:08","date_gmt":"2023-07-27T15:00:08","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%8f%e1%85%a9%e1%84%89%e1%85%a1%e1%84%8b%e1%85%b5%e1%86%ab-%e1%84%8b%e1%85%b2%e1%84%89%e1%85%a1%e1%84%89%e1%85%a5%e1%86%bc-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab\/"},"modified":"2023-07-27T15:00:08","modified_gmt":"2023-07-27T15:00:08","slug":"%e1%84%8f%e1%85%a9%e1%84%89%e1%85%a1%e1%84%8b%e1%85%b5%e1%86%ab-%e1%84%8b%e1%85%b2%e1%84%89%e1%85%a1%e1%84%89%e1%85%a5%e1%86%bc-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%8f%e1%85%a9%e1%84%89%e1%85%a1%e1%84%8b%e1%85%b5%e1%86%ab-%e1%84%8b%e1%85%b2%e1%84%89%e1%85%a1%e1%84%89%e1%85%a5%e1%86%bc-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab\/","title":{"rendered":"Python\uc5d0\uc11c \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740<\/strong> \ub0b4\ubd80 \uacf1 \uacf5\uac04\uc758 \ub450 \ubca1\ud130 \uac04\uc758 \uc720\uc0ac\uc131\uc744 \uce21\uc815\ud55c \uac83\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub450 \ubca1\ud130 A\uc640 B\uc758 \uacbd\uc6b0 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \ub2e4\uc74c\uacfc \uac19\uc774 \uacc4\uc0b0\ub429\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131<\/strong> = \u03a3A <sub>i<\/sub> B <sub>i<\/sub> \/ (\u221a\u03a3A <sub>i<\/sub> <sup>2<\/sup> \u221a\u03a3B <sub>i<\/sub> <sup>2<\/sup> )<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 <a href=\"https:\/\/numpy.org\/doc\/stable\/index.html\" target=\"_blank\" rel=\"noopener noreferrer\">NumPy<\/a> \ub77c\uc774\ube0c\ub7ec\ub9ac\uc758 \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec Python\uc5d0\uc11c \ubca1\ud130 \uac04\uc758 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Python\uc5d0\uc11c \ub450 \ubca1\ud130 \uac04\uc758 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 Python\uc5d0\uc11c \ub450 \ubc30\uc5f4 \uac04\uc758 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">from<\/span> numpy <span style=\"color: #008000;\">import<\/span> dot\n<span style=\"color: #008000;\">from<\/span> numpy. <span style=\"color: #3366ff;\">linalg<\/span> <span style=\"color: #008000;\">import<\/span> norm\n\n<span style=\"color: #008080;\">#define arrays\n<\/span>a = [23, 34, 44, 45, 42, 27, 33, 34]\nb = [17, 18, 22, 26, 26, 29, 31, 30]\n\n<span style=\"color: #008080;\">#calculate Cosine Similarity\n<\/span>cos_sim = <span style=\"color: #3366ff;\">dot<\/span> (a, b)\/( <span style=\"color: #3366ff;\">norm<\/span> (a)* <span style=\"color: #3366ff;\">norm<\/span> (b))\n\ncos_sim\n\n0.965195008357566\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub450 \ud14c\uc774\ube14 \uac04\uc758 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 <strong>0.965195<\/strong> \uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \ubc29\ubc95\uc740 \uae38\uc774\uc5d0 \uad00\uacc4\uc5c6\uc774 \ub450 \uac1c\uc758 \ubc30\uc5f4\uc5d0\uc11c \uc791\ub3d9\ud569\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import <span style=\"color: #000000;\">numpy<\/span> as <span style=\"color: #000000;\">np<\/span>\nfrom<\/span> numpy <span style=\"color: #008000;\">import<\/span> dot\n<span style=\"color: #008000;\">from<\/span> numpy. <span style=\"color: #3366ff;\">linalg<\/span> <span style=\"color: #008000;\">import<\/span> norm\n\n<span style=\"color: #008080;\">#define arrays\n<\/span>a = np.random.randint(10, size= <span style=\"color: #008000;\">100<\/span> )\nb = np.random.randint(10, size= <span style=\"color: #008000;\">100<\/span> )\n\n<span style=\"color: #008080;\">#calculate Cosine Similarity\n<\/span>cos_sim = <span style=\"color: #3366ff;\">dot<\/span> (a, b)\/( <span style=\"color: #3366ff;\">norm<\/span> (a)* <span style=\"color: #3366ff;\">norm<\/span> (b))\n\ncos_sim\n\n0.7340201613960431<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uadf8\ub7ec\ub098 \uc774\ub294 \ub450 \ubc30\uc5f4\uc758 \uae38\uc774\uac00 \ub3d9\uc77c\ud55c \uacbd\uc6b0\uc5d0\ub9cc \uc791\ub3d9\ud569\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import <span style=\"color: #000000;\">numpy<\/span> as <span style=\"color: #000000;\">np<\/span>\nfrom<\/span> numpy <span style=\"color: #008000;\">import<\/span> dot\n<span style=\"color: #008000;\">from<\/span> numpy. <span style=\"color: #3366ff;\">linalg<\/span> <span style=\"color: #008000;\">import<\/span> norm\n\n<span style=\"color: #008080;\">#define arrays\n<\/span>a = np.random.randint(10, size= <span style=\"color: #008000;\">90<\/span> ) <span style=\"color: #008080;\">#length=90<\/span>\nb = np.random.randint(10, size= <span style=\"color: #008000;\">100<\/span> ) <span style=\"color: #008080;\">#length=100<\/span>\n\n<span style=\"color: #008080;\">#calculate Cosine Similarity\n<\/span>cos_sim = <span style=\"color: #3366ff;\">dot<\/span> (a, b)\/( <span style=\"color: #3366ff;\">norm<\/span> (a)* <span style=\"color: #3366ff;\">norm<\/span> (b))\n\ncos_sim\n\n<span style=\"color: #993300;\">ValueError<\/span> : shapes (90,) and (100,) not aligned: 90 (dim 0) != 100 (dim 0)\n<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\ucf54\uba58\ud2b8<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\"><strong>1.<\/strong> Python\uc744 \uc0ac\uc6a9\ud558\uc5ec \ucf54\uc0ac\uc778 \uc720\uc0ac\ub3c4\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95\uc5d0\ub294 \uc5ec\ub7ec \uac00\uc9c0\uac00 \uc788\uc9c0\ub9cc <a href=\"https:\/\/stackoverflow.com\/questions\/18424228\/cosine-similarity-between-2-number-lists\" target=\"_blank\" rel=\"noopener noreferrer\">\uc774 Stack Overflow \uc2a4\ub808\ub4dc<\/a> \uc5d0\uc11c \uc124\uba85\ud558\ub4ef\uc774 \uc774 \uae30\uc0ac\uc5d0\uc11c \uc124\uba85\ud558\ub294 \ubc29\ubc95\uc774 \uac00\uc7a5 \ube60\ub978 \uac83\uc73c\ub85c \ub098\ud0c0\ub0ac\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>2.<\/strong> \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\ub824\uba74<a href=\"https:\/\/en.wikipedia.org\/wiki\/Cosine_similarity\" target=\"_blank\" rel=\"noopener noreferrer\">\uc774 Wikipedia \ud398\uc774\uc9c0\ub97c<\/a> \ucc38\uc870\ud558\uc138\uc694.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \ub0b4\ubd80 \uacf1 \uacf5\uac04\uc758 \ub450 \ubca1\ud130 \uac04\uc758 \uc720\uc0ac\uc131\uc744 \uce21\uc815\ud55c \uac83\uc785\ub2c8\ub2e4. \ub450 \ubca1\ud130 A\uc640 B\uc758 \uacbd\uc6b0 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \ub2e4\uc74c\uacfc \uac19\uc774 \uacc4\uc0b0\ub429\ub2c8\ub2e4. \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131 = \u03a3A i B i \/ (\u221a\u03a3A i 2 \u221a\u03a3B i 2 ) \uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 NumPy \ub77c\uc774\ube0c\ub7ec\ub9ac\uc758 \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec Python\uc5d0\uc11c \ubca1\ud130 \uac04\uc758 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4. Python\uc5d0\uc11c \ub450 \ubca1\ud130 \uac04\uc758 \ucf54\uc0ac\uc778 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[],"class_list":["post-1113","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Python\uc5d0\uc11c \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95 - \ud1b5\uacc4\ud559<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \ub3d9\uc77c\ud55c \ubc29\uc2dd\uc73c\ub85c \ucf54\uc0ac\uc778\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95\uc744 \uc608\uc81c\uc640 \ud568\uaed8 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ko\/\u110f\u1169\u1109\u1161\u110b\u1175\u11ab-\u110b\u1172\u1109\u1161\u1109\u1165\u11bc-\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Python\uc5d0\uc11c \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95 - 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