{"id":25167,"date":"2024-10-26T09:52:42","date_gmt":"2024-10-26T09:52:42","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=25167"},"modified":"2024-11-26T08:02:39","modified_gmt":"2024-11-26T08:02:39","slug":"%eb%94%a5-%eb%9f%ac%eb%8b%9d%ec%9d%84-%ec%9d%b4%ec%9a%a9%ed%95%9c-%ec%9e%90%ec%97%b0%ec%96%b4-%ec%b2%98%eb%a6%ac-%ed%8c%90%eb%8b%a4%ec%8a%a4-%eb%84%98%ed%8c%8c%ec%9d%b4-%eb%a7%b7%ed%94%8c%eb%a1%af","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/25167\/","title":{"rendered":"\ub525 \ub7ec\ub2dd\uc744 \uc774\uc6a9\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac: \ud310\ub2e4\uc2a4, \ub118\ud30c\uc774, \ub9f7\ud50c\ub86f\ub9bd"},"content":{"rendered":"<p><body><\/p>\n<p>\uc790\uc5f0\uc5b4 \ucc98\ub9ac(Natural Language Processing, NLP)\ub294 \uc778\uacf5\uc9c0\ub2a5\uc758 \ud55c \ubd84\uc57c\ub85c, \ucef4\ud4e8\ud130\uac00 \uc778\uac04\uc758 \uc5b8\uc5b4\ub97c \uc774\ud574\ud558\uace0 \ucc98\ub9ac\ud558\ub294 \ubc29\ubc95\uc744 \uc5f0\uad6c\ud569\ub2c8\ub2e4. \ucd5c\uadfc \uba87 \ub144 \ub3d9\uc548, \ub525 \ub7ec\ub2dd\uc758 \ubc1c\uc804\uc73c\ub85c NLP \uae30\uc220\uc774 \ube60\ub974\uac8c \ubc1c\uc804\ud558\uace0 \uc788\uc73c\uba70, \uc774\ub294 \ubb38\uc7a5 \uc0dd\uc131, \uac10\uc815 \ubd84\uc11d, \uae30\uacc4 \ubc88\uc5ed \ub4f1 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0\uc11c \ud65c\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \ub525 \ub7ec\ub2dd\uc744 \uc774\uc6a9\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc758 \uae30\ubcf8 \uac1c\ub150\uacfc \ud568\uaed8 \ub370\uc774\ud130 \ubd84\uc11d \ubc0f \uc2dc\uac01\ud654\uc5d0 \uc720\uc6a9\ud55c <strong>\ud310\ub2e4\uc2a4(Pandas)<\/strong>, <strong>\ub118\ud30c\uc774(Numpy)<\/strong>, <strong>\ub9f7\ud50c\ub86f\ub9bd(Matplotlib)<\/strong> \ub77c\uc774\ube0c\ub7ec\ub9ac\uc758 \uc0ac\uc6a9\ubc95\uc744 \uc18c\uac1c\ud558\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>1. \uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc758 \uae30\ucd08<\/h2>\n<p>\uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc758 \ubaa9\ud45c\ub294 \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\ub97c \ubd84\uc11d\ud558\uace0 \uc758\ubbf8\ub97c \uc774\ud574\ud558\uc5ec \uc778\uac04\uc758 \uc5b8\uc5b4\ub97c \ucc98\ub9ac\ud558\ub294 \uac83\uc785\ub2c8\ub2e4. \uc774\ub294 \uc8fc\ub85c \ub2e4\uc74c\uacfc \uac19\uc740 \ud0dc\uc2a4\ud06c\ub4e4\ub85c \ub098\ub20c \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/p>\n<ul>\n<li>\ud14d\uc2a4\ud2b8 \ubd84\ub958<\/li>\n<li>\uac10\uc815 \ubd84\uc11d<\/li>\n<li>\uae30\uacc4 \ubc88\uc5ed<\/li>\n<li>\ubb38\uc11c \uc694\uc57d<\/li>\n<li>\uc9c8\ubb38 \uc751\ub2f5 \uc2dc\uc2a4\ud15c<\/li>\n<\/ul>\n<h2>2. \ub525 \ub7ec\ub2dd\uc758 \uc5ed\ud560<\/h2>\n<p>\ub525 \ub7ec\ub2dd\uc740 \ub370\uc774\ud130\uc758 \ud328\ud134\uc744 \uc790\ub3d9\uc73c\ub85c \ud559\uc2b5\ud558\ub294 \ubc29\ubc95\uc73c\ub85c, \ud2b9\ud788 \ub300\uaddc\ubaa8 \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud558\ub294 \ub370 \ud6a8\uacfc\uc801\uc785\ub2c8\ub2e4. \ub525 \ub7ec\ub2dd \ubaa8\ub378\uc740 \uc778\uacf5 \uc2e0\uacbd\ub9dd\uc744 \uae30\ubc18\uc73c\ub85c \ud558\uba70, \uc5ec\ub7ec \uce35\uc758 \ub274\ub7f0\uc774 \uc5f0\uacb0\ub418\uc5b4 \ubcf5\uc7a1\ud55c \uae30\ub2a5\uc744 \ud559\uc2b5\ud569\ub2c8\ub2e4. \ub525 \ub7ec\ub2dd\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc790\uc5f0\uc5b4 \ucc98\ub9ac \uc791\uc5c5\uc744 \uc218\ud589\ud560 \ub54c \uc8fc\ub85c \uc0ac\uc6a9\ub418\ub294 \ubaa8\ub378\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:<\/p>\n<ul>\n<li>\uc21c\ud658 \uc2e0\uacbd\ub9dd(Recurrent Neural Networks, RNN)<\/li>\n<li>\uc7a5\ub2e8\uae30 \uae30\uc5b5 \ub124\ud2b8\uc6cc\ud06c(Long Short-Term Memory, LSTM)<\/li>\n<li>\ubcc0\ud615\uae30(Transformer)<\/li>\n<\/ul>\n<h2>3. \ub370\uc774\ud130 \ubd84\uc11d\uacfc \uc0ac\uc804 \ucc98\ub9ac<\/h2>\n<p>\uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc5d0 \uc0ac\uc6a9\ub418\ub294 \ub370\uc774\ud130\ub294 \uc77c\ubc18\uc801\uc73c\ub85c \ube44\uc815\ud615 \ud14d\uc2a4\ud2b8 \ud615\uc2dd\uc73c\ub85c, \ub370\uc774\ud130\ub97c \ubd84\uc11d\ud558\uace0 \ubaa8\ub378\uc5d0 \ub9de\uac8c \ubcc0\ud658\ud558\ub294 \uacfc\uc815\uc774 \ud544\uc694\ud569\ub2c8\ub2e4. \uc774\ub97c \uc704\ud574 <strong>\ud310\ub2e4\uc2a4(Pandas)<\/strong>\uc640 <strong>\ub118\ud30c\uc774(Numpy)<\/strong>\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<h3>3.1 \ud310\ub2e4\uc2a4(Pandas)<\/h3>\n<p>\ud310\ub2e4\uc2a4\ub294 \ub370\uc774\ud130 \uc870\uc791 \ubc0f \ubd84\uc11d\uc744 \uc704\ud55c \ud30c\uc774\uc36c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub85c, \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\ub97c \uc815\ub9ac\ud558\uace0 \ucc98\ub9ac\ud558\ub294 \ub370 \ud544\uc218\uc801\uc778 \ub3c4\uad6c\uc785\ub2c8\ub2e4. \ub2e4\uc74c\uc740 \uae30\ubcf8\uc801\uc778 \ud310\ub2e4\uc2a4 \uc0ac\uc6a9\ubc95\uc785\ub2c8\ub2e4:<\/p>\n<h4>3.1.1 \ub370\uc774\ud130\ud504\ub808\uc784 \uc0dd\uc131<\/h4>\n<pre><code>import pandas as pd\n\ndata = {\n    'text': ['\ub098\ub294 \uc624\ub298 \uae30\ubd84\uc774 \uc88b\ub2e4.', '\uc815\ub9d0 \uc88b\uc740 \ub0a0\uc528\ub2e4.', '\ub525 \ub7ec\ub2dd\uc740 \uc7ac\ubbf8\uc788\ub2e4.'],\n    'label': [1, 1, 1]\n}\n\ndf = pd.DataFrame(data)\nprint(df)<\/code><\/pre>\n<h4>3.1.2 \ub370\uc774\ud130 \ud544\ud130\ub9c1<\/h4>\n<pre><code>happy_texts = df[df['label'] == 1]\nprint(happy_texts)<\/code><\/pre>\n<h3>3.2 \ub118\ud30c\uc774(Numpy)<\/h3>\n<p>\ub118\ud30c\uc774\ub294 \uc218\uce58 \uacc4\uc0b0\uc744 \uc704\ud55c \ud30c\uc774\uc36c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub85c, \ubc30\uc5f4 \ubc0f \ud589\ub82c \uc5f0\uc0b0\uc744 \uc27d\uac8c \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd\uc5d0\uc11c \ub9ce\uc740 \uc22b\uc790 \uacc4\uc0b0\uc744 \ud544\uc694\ub85c \ud560 \ub54c \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \ubca1\ud130\ud654\ub41c \ud14d\uc2a4\ud2b8 \ud45c\ud604\uc744 \ub9cc\ub4e4\uae30 \uc704\ud574 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<h4>3.2.1 \ubc30\uc5f4 \uc0dd\uc131<\/h4>\n<pre><code>import numpy as np\n\narray = np.array([1, 2, 3, 4, 5])\nprint(array)<\/code><\/pre>\n<h2>4. \ub370\uc774\ud130 \uc2dc\uac01\ud654<\/h2>\n<p>\ub370\uc774\ud130\ub97c \ubd84\uc11d\ud560 \ub54c \uc2dc\uac01\ud654\ub294 \uc911\uc694\ud55c \uc5ed\ud560\uc744 \ud569\ub2c8\ub2e4. <strong>\ub9f7\ud50c\ub86f\ub9bd(Matplotlib)<\/strong> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub370\uc774\ud130\ub97c \uc2dc\uac01\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<h3>4.1 \uac04\ub2e8\ud55c \uc2dc\uac01\ud654 \uc0dd\uc131<\/h3>\n<pre><code>import matplotlib.pyplot as plt\n\nlabels = ['Text A', 'Text B', 'Text C']\nsizes = [15, 30, 45]\n\nplt.pie(sizes, labels=labels, autopct='%1.1f%%')\nplt.axis('equal')\nplt.title('\ud14d\uc2a4\ud2b8 \ube44\uc728 \uadf8\ub798\ud504')\nplt.show()<\/code><\/pre>\n<h2>5. \ub525 \ub7ec\ub2dd \ubaa8\ub378 \uad6c\ucd95<\/h2>\n<p>\uc774\uc81c \uc6b0\ub9ac\ub294 \uc790\uc5f0\uc5b4 \ucc98\ub9ac\ub97c \uc704\ud55c \uae30\ubcf8 \uc900\ube44\uac00 \ub418\uc5c8\uc2b5\ub2c8\ub2e4. Keras\uc640 TensorFlow\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub525 \ub7ec\ub2dd \ubaa8\ub378\uc744 \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\uc74c\uc740 \uac04\ub2e8\ud55c LSTM \ubaa8\ub378\uc758 \uc608\uc81c\uc785\ub2c8\ub2e4:<\/p>\n<pre><code>from tensorflow.keras.models import Sequential\nfrom tensorflow.keras.layers import LSTM, Dense, Embedding\n\nmodel = Sequential()\nmodel.add(Embedding(input_dim=1000, output_dim=64))\nmodel.add(LSTM(128))\nmodel.add(Dense(1, activation='sigmoid'))\n\nmodel.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])<\/code><\/pre>\n<h2>6. \uacb0\ub860<\/h2>\n<p>\ub525 \ub7ec\ub2dd\uc744 \uc774\uc6a9\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac \uae30\uc220\uc740 \ube44\uc988\ub2c8\uc2a4\uc640 \uc5f0\uad6c\uc5d0 \ud070 \uc601\ud5a5\uc744 \ubbf8\uce58\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ud310\ub2e4\uc2a4, \ub118\ud30c\uc774, \ub9f7\ud50c\ub86f\ub9bd\uacfc \uac19\uc740 \ub3c4\uad6c\ub294 \ub370\uc774\ud130 \ubd84\uc11d\uacfc \uc2dc\uac01\ud654\uc5d0 \ud544\uc218\uc801\uc774\uba70, \uc774\ub97c \ud1b5\ud574 \uc6b0\ub9ac\ub294 \ud6a8\uacfc\uc801\uc778 \ubaa8\ub378\uc744 \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc55e\uc73c\ub85c \uc774\ub7ec\ud55c \uae30\uc220\uc740 \ub354\uc6b1 \ubc1c\uc804\ud560 \uac83\uc774\uba70, \ub354 \ub9ce\uc740 \ub370\uc774\ud130\uc640 \ubcf5\uc7a1\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubb38\uc81c\ub97c \ud574\uacb0\ud560 \uc218 \uc788\ub294 \uae30\ud68c\uac00 \ub9ce\uc544\uc9c8 \uac83\uc785\ub2c8\ub2e4.<\/p>\n<h2>7. \ucc38\uace0 \ubb38\ud5cc<\/h2>\n<ul>\n<li>\ud55c\ube5b\ubbf8\ub514\uc5b4, &#8220;\ud30c\uc774\uc36c\uacfc \ud310\ub2e4\uc2a4 \ud55c \ubc88\uc5d0 \ubc30\uc6b0\uae30&#8221;, 2020.<\/li>\n<li>MIT Press, &#8220;Deep Learning&#8221;, Ian Goodfellow, Yoshua Bengio, Aaron Courville, 2016.<\/li>\n<li>O&#8217;Reilly, &#8220;Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow&#8221;, Aur\u00e9lien G\u00e9ron, 2019.<\/li>\n<\/ul>\n<p><\/body><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\uc790\uc5f0\uc5b4 \ucc98\ub9ac(Natural Language Processing, NLP)\ub294 \uc778\uacf5\uc9c0\ub2a5\uc758 \ud55c \ubd84\uc57c\ub85c, \ucef4\ud4e8\ud130\uac00 \uc778\uac04\uc758 \uc5b8\uc5b4\ub97c \uc774\ud574\ud558\uace0 \ucc98\ub9ac\ud558\ub294 \ubc29\ubc95\uc744 \uc5f0\uad6c\ud569\ub2c8\ub2e4. \ucd5c\uadfc \uba87 \ub144 \ub3d9\uc548, \ub525 \ub7ec\ub2dd\uc758 \ubc1c\uc804\uc73c\ub85c NLP \uae30\uc220\uc774 \ube60\ub974\uac8c \ubc1c\uc804\ud558\uace0 \uc788\uc73c\uba70, \uc774\ub294 \ubb38\uc7a5 \uc0dd\uc131, \uac10\uc815 \ubd84\uc11d, \uae30\uacc4 \ubc88\uc5ed \ub4f1 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0\uc11c \ud65c\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \ub525 \ub7ec\ub2dd\uc744 \uc774\uc6a9\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc758 \uae30\ubcf8 \uac1c\ub150\uacfc \ud568\uaed8 \ub370\uc774\ud130 \ubd84\uc11d \ubc0f \uc2dc\uac01\ud654\uc5d0 \uc720\uc6a9\ud55c \ud310\ub2e4\uc2a4(Pandas), &hellip; <a href=\"https:\/\/atmokpo.com\/w\/25167\/\" class=\"more-link\">\ub354 \ubcf4\uae30<span class=\"screen-reader-text\"> &#8220;\ub525 \ub7ec\ub2dd\uc744 \uc774\uc6a9\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac: \ud310\ub2e4\uc2a4, \ub118\ud30c\uc774, \ub9f7\ud50c\ub86f\ub9bd&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[16],"tags":[],"class_list":["post-25167","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\ub525 \ub7ec\ub2dd\uc744 \uc774\uc6a9\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac: \ud310\ub2e4\uc2a4, \ub118\ud30c\uc774, \ub9f7\ud50c\ub86f\ub9bd - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/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:\/\/atmokpo.com\/w\/25167\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\ub525 \ub7ec\ub2dd\uc744 \uc774\uc6a9\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac: \ud310\ub2e4\uc2a4, \ub118\ud30c\uc774, \ub9f7\ud50c\ub86f\ub9bd - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"\uc790\uc5f0\uc5b4 \ucc98\ub9ac(Natural Language Processing, NLP)\ub294 \uc778\uacf5\uc9c0\ub2a5\uc758 \ud55c \ubd84\uc57c\ub85c, \ucef4\ud4e8\ud130\uac00 \uc778\uac04\uc758 \uc5b8\uc5b4\ub97c \uc774\ud574\ud558\uace0 \ucc98\ub9ac\ud558\ub294 \ubc29\ubc95\uc744 \uc5f0\uad6c\ud569\ub2c8\ub2e4. \ucd5c\uadfc \uba87 \ub144 \ub3d9\uc548, \ub525 \ub7ec\ub2dd\uc758 \ubc1c\uc804\uc73c\ub85c NLP \uae30\uc220\uc774 \ube60\ub974\uac8c \ubc1c\uc804\ud558\uace0 \uc788\uc73c\uba70, \uc774\ub294 \ubb38\uc7a5 \uc0dd\uc131, \uac10\uc815 \ubd84\uc11d, \uae30\uacc4 \ubc88\uc5ed \ub4f1 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0\uc11c \ud65c\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \ub525 \ub7ec\ub2dd\uc744 \uc774\uc6a9\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc758 \uae30\ubcf8 \uac1c\ub150\uacfc \ud568\uaed8 \ub370\uc774\ud130 \ubd84\uc11d \ubc0f \uc2dc\uac01\ud654\uc5d0 \uc720\uc6a9\ud55c \ud310\ub2e4\uc2a4(Pandas), &hellip; \ub354 \ubcf4\uae30 &quot;\ub525 \ub7ec\ub2dd\uc744 \uc774\uc6a9\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac: \ud310\ub2e4\uc2a4, \ub118\ud30c\uc774, \ub9f7\ud50c\ub86f\ub9bd&quot;\" \/>\n<meta property=\"og:url\" content=\"https:\/\/atmokpo.com\/w\/25167\/\" \/>\n<meta property=\"og:site_name\" content=\"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"article:published_time\" content=\"2024-10-26T09:52:42+00:00\" \/>\n<meta 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