2023\ub144 10\uc6d4 3\uc77c | \ud2b8\ub808\uc774\ub529 | \uba38\uc2e0\ub7ec\ub2dd | \ub525\ub7ec\ub2dd<\/p>\n<\/header>\n \ucd5c\uadfc \uba87 \ub144\uac04 \uae08\uc735 \uc2dc\uc7a5\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd \uae30\uc220\uc774 \uae09\uc18d\ub3c4\ub85c \ubc1c\uc804\ud558\uba74\uc11c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc5d0 \ud070 \uc601\ud5a5\uc744 \ubbf8\uce58\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \uae30\ubcf8 \uac1c\ub150\uacfc \ubc29\ubc95\ub860\uc744 \uc18c\uac1c\ud558\uace0, \uc624\ud508\ud14c\uc774\ube14 \ub370\uc774\ud130\ub97c \uc2a4\ud06c\ub798\ud551\ud558\uc5ec \ud2b8\ub808\uc774\ub529 \uc804\ub7b5\uc5d0 \ud65c\uc6a9\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n<\/section>\n \uba38\uc2e0\ub7ec\ub2dd\uc740 \ucef4\ud4e8\ud130\uac00 \ub370\uc774\ud130\ub97c \ud1b5\ud574 \uc2a4\uc2a4\ub85c \ud559\uc2b5\ud558\uace0 \uac1c\uc120\ud560 \uc218 \uc788\ub294 \uae30\uc220\uc774\uba70, \uc8fc\uc5b4\uc9c4 \ub370\uc774\ud130\uc5d0\uc11c \ud328\ud134\uc744 \uc778\uc2dd\ud558\uac70\ub098 \uc608\uce21\ud558\ub294 \ub370 \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uae30\uc220\uc740 \uae08\uc735 \uc2dc\uc7a5\uc5d0\uc11c\ub3c4 \ub110\ub9ac \ud65c\uc6a9\ub429\ub2c8\ub2e4.<\/p>\n \ub525\ub7ec\ub2dd\uc740 \uba38\uc2e0\ub7ec\ub2dd\uc758 \ud55c \ubd84\uc57c\ub85c, \uc778\uacf5\uc2e0\uacbd\ub9dd\uc744 \uae30\ubc18\uc73c\ub85c \ud55c \ud559\uc2b5 \ubc29\ubc95\uc785\ub2c8\ub2e4. \ud2b9\ud788 \ub300\ub7c9\uc758 \ub370\uc774\ud130\uc5d0\uc11c \ub192\uc740 \uc131\ub2a5\uc744 \ubc1c\ud718\ud558\uc5ec \uc774\ubbf8\uc9c0 \uc778\uc2dd, \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ub4f1 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0\uc11c \uc131\uacf5\uc801\uc778 \uacb0\uacfc\ub97c \ubcf4\uc5ec\uc8fc\uace0 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd\uc740 \uac01\uac01\uc758 \uc7a5\ub2e8\uc810\uc774 \uc874\uc7ac\ud569\ub2c8\ub2e4. \uba38\uc2e0\ub7ec\ub2dd\uc740 \uc77c\ubc18\uc801\uc73c\ub85c \ub370\uc774\ud130\uac00 \uc801\uace0 \uac04\ub2e8\ud55c \ubb38\uc81c\uc5d0 \ud6a8\uacfc\uc801\uc774\uba70, \ub525\ub7ec\ub2dd\uc740 \ub300\ub7c9\uc758 \ub370\uc774\ud130\uc5d0\uc11c \ubcf5\uc7a1\ud55c \ud328\ud134\uc744 \uc778\uc2dd\ud558\ub294 \ub370 \uc6b0\uc218\ud55c \uc131\ub2a5\uc744 \ubcf4\uc785\ub2c8\ub2e4.<\/p>\n<\/section>\n \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc740 \uc77c\uc815\ud55c \uaddc\uce59\uc5d0 \ub530\ub77c \uc790\ub3d9\uc73c\ub85c \ub9e4\ub9e4\ub97c \uc218\ud589\ud558\ub294 \uc2dc\uc2a4\ud15c\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 \uc778\uac04\uc758 \uac10\uc815\uc801 \uc694\uc18c\ub97c \ubc30\uc81c\ud558\uace0 \uc77c\uad00\ub41c \ud22c\uc790 \uc804\ub7b5\uc744 \uc2e4\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc5d0\ub294 \ub2e4\uc591\ud55c \uc811\uadfc \ubc29\uc2dd\uc774 \uc788\uc73c\uba70, \uadf8 \uc911 \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd \uae30\ubc18\uc758 \ubaa8\ub378\ub3c4 \ud3ec\ud568\ub429\ub2c8\ub2e4.<\/p>\n \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998\uc744 \uad6c\ucd95\ud558\uae30 \uc704\ud574 \uc6b0\uc120\uc801\uc73c\ub85c \ud544\uc694\ud55c \uac83\uc740 \ub370\uc774\ud130\uc785\ub2c8\ub2e4. \uae08\uc735 \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud558\uae30 \uc704\ud55c \ubc29\ubc95 \uc911 \ud558\ub098\ub294 \uc624\ud508\ud14c\uc774\ube14(OpenTable)\uacfc \uac19\uc740 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uc2a4\ud06c\ub798\ud551\ud558\ub294 \uac83\uc785\ub2c8\ub2e4. \uc624\ud508\ud14c\uc774\ube14\uc740 \ub808\uc2a4\ud1a0\ub791 \uc608\uc57d \uc11c\ube44\uc2a4\ub97c \uc81c\uacf5\ud558\ub294 \ud50c\ub7ab\ud3fc\uc73c\ub85c, \ub2e4\uc591\ud55c \ub808\uc2a4\ud1a0\ub791 \uc815\ubcf4\uc640 \ud3c9\uac00 \ub370\uc774\ud130\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/p>\n \ub370\uc774\ud130 \uc2a4\ud06c\ub798\ud551\uc740 \uc6f9\uc5d0\uc11c \ud544\uc694\ud55c \uc815\ubcf4\ub97c \uc790\ub3d9\uc73c\ub85c \ucd94\ucd9c\ud558\ub294 \uacfc\uc815\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4. Python\uc758 BeautifulSoup, Scrapy \ub4f1\uc758 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc624\ud508\ud14c\uc774\ube14\uc5d0\uc11c \ub808\uc2a4\ud1a0\ub791 \uc815\ubcf4\ub97c \uc2a4\ud06c\ub798\ud551\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n \ud2b9\uc131 \uacf5\ud559(Feature Engineering)\uc740 \ub370\uc774\ud130\ub97c \ud6a8\uacfc\uc801\uc73c\ub85c \ud65c\uc6a9\ud558\uae30 \uc704\ud574 \ud2b9\uc9d5\uc744 \uc120\ud0dd\ud558\uac70\ub098 \ubcc0\ud615\ud558\ub294 \uacfc\uc815\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4. \ud2b8\ub808\uc774\ub529\uc5d0 \ud544\uc694\ud55c \uc720\uc6a9\ud55c \uc815\ubcf4\ub97c \uc5bb\uae30 \uc704\ud574 \ub2e4\uc591\ud55c \ubcc0\uc218\ub4e4\uc744 \uc0dd\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n \uba38\uc2e0\ub7ec\ub2dd\uc5d0\uc11c\ub294 \uc120\ud615 \ud68c\uadc0, \uacb0\uc815 \ud2b8\ub9ac, \ub79c\ub364 \ud3ec\ub808\uc2a4\ud2b8 \ub4f1\uc758 \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc73c\uba70, \ub525\ub7ec\ub2dd\uc5d0\uc11c\ub294 LSTM, CNN \uac19\uc740 \ub124\ud2b8\uc6cc\ud06c \uad6c\uc870\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uac01 \ubaa8\ub378\uc758 \uc7a5\ub2e8\uc810\uc744 \uc774\ud574\ud558\uace0 \uc801\uc808\ud55c \ubaa8\ub378\uc744 \uc120\ud0dd\ud558\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4.<\/p>\n<\/section>\n \uc2a4\ud06c\ub798\ud551\ud55c \ub370\uc774\ud130\ub294 \uc885\uc885 \uc815\uc81c\ub418\uc9c0 \uc54a\uc740 \uc0c1\ud0dc\ub85c \uc874\uc7ac\ud569\ub2c8\ub2e4. \ub530\ub77c\uc11c \uc804\ucc98\ub9ac \uacfc\uc815\uc774 \ud544\uc694\ud569\ub2c8\ub2e4. \uacb0\uce21\uac12 \ucc98\ub9ac, \uc774\uc0c1\uce58 \uc81c\uac70, \ud615\ubcc0\ud658 \ub4f1\uc744 \ud1b5\ud574 \ub370\uc774\ud130\uc758 \ud488\uc9c8\uc744 \ub192\uc77c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/section>\n \ub370\uc774\ud130\uac00 \uc900\ube44\ub418\uba74, \uba38\uc2e0\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998\uc744 \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub378\uc744 \ud6c8\ub828\uc2dc\ud0b5\ub2c8\ub2e4. \uc774 \uacfc\uc815\uc5d0\uc11c \ub370\uc774\ud130\ub97c \ud6c8\ub828 \uc138\ud2b8\uc640 \uac80\uc99d \uc138\ud2b8\ub85c \ub098\ub204\uc5b4 \ubaa8\ub378\uc758 \uc77c\ubc18\ud654 \uc131\ub2a5\uc744 \ud3c9\uac00\ud569\ub2c8\ub2e4.<\/p>\n \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc740 \uae08\uc735 \uc2dc\uc7a5\uc758 \ubcc0\ub3d9\uc131\uc744 \uc608\uce21\ud558\ub294 \ub370 \ud070 \ub3c4\uc6c0\uc774 \ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc624\ud508\ud14c\uc774\ube14 \ub370\uc774\ud130 \uc2a4\ud06c\ub798\ud551\uc744 \ud1b5\ud574 \uc720\uc6a9\ud55c \uc778\uc0ac\uc774\ud2b8\ub97c \uc5bb\uc744 \uc218 \uc788\uc73c\uba70, \ub2e4\uc591\ud55c \ubaa8\ub378\uc744 \uc2e4\ud5d8\ud558\uc5ec \ub354 \ub098\uc740 \uc131\uacfc\ub97c \uc5bb\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n \ud5a5\ud6c4 \uc5f0\uad6c \ubc29\ud5a5\uc73c\ub85c\ub294 \uac15\ud654\ud559\uc2b5\uc744 \ud65c\uc6a9\ud55c \ud2b8\ub808\uc774\ub529 \uc804\ub7b5 \uac1c\ubc1c, \ub300\ub7c9\uc758 \uc2e4\uc2dc\uac04 \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud558\ub294 \ubc29\ubc95\ub860 \uc5f0\uad6c, \ub2e4\uc591\ud55c \uc2dc\uc7a5 \uc870\uac74\uc5d0\uc11c\uc758 \ubaa8\ub378 \uc131\ub2a5 \uac80\uc99d \ub4f1\uc774 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/section>\n1. \uc11c\ub860<\/h2>\n
2. \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd\uc758 \uae30\ucd08<\/h2>\n
2.1 \uba38\uc2e0\ub7ec\ub2dd\uc758 \uc815\uc758<\/h3>\n
2.2 \ub525\ub7ec\ub2dd\uc758 \uc815\uc758<\/h3>\n
2.3 \uba38\uc2e0\ub7ec\ub2dd vs. \ub525\ub7ec\ub2dd<\/h3>\n
3. \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \uae30\ubcf8 \uac1c\ub150<\/h2>\n
3.1 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \uc7a5\uc810<\/h3>\n
\n
3.2 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \ub2e8\uc810<\/h3>\n
\n
4. \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd\uc744 \uc774\uc6a9\ud55c \ud2b8\ub808\uc774\ub529 \uc804\ub7b5<\/h2>\n
4.1 \ub370\uc774\ud130 \uc218\uc9d1<\/h3>\n
4.1.1 \ub370\uc774\ud130 \uc2a4\ud06c\ub798\ud551<\/h4>\n
4.2 \ud2b9\uc131 \uacf5\ud559<\/h3>\n
4.3 \ubaa8\ub378 \uc120\ud0dd<\/h3>\n
5. \uc624\ud508\ud14c\uc774\ube14 \ub370\uc774\ud130 \uc2a4\ud06c\ub798\ud551 \uc2e4\uc2b5<\/h2>\n
5.1 \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac \uc124\uce58<\/h3>\n
\n
\n pip install requests beautifulsoup4 pandas\n <\/code>\n <\/pre>\n5.2 \ub370\uc774\ud130 \uc2a4\ud06c\ub798\ud551 \ucf54\ub4dc \uc608\uc2dc<\/h3>\n
\n
\n import requests\n from bs4 import BeautifulSoup\n import pandas as pd\n\n url = 'https:\/\/www.opentable.com\/'\n response = requests.get(url)\n soup = BeautifulSoup(response.text, 'html.parser')\n\n restaurants = []\n for restaurant in soup.find_all('div', class_='restaurant-details'):\n name = restaurant.find('h2').text\n rating = restaurant.find('span', class_='rating').text\n restaurants.append({'name': name, 'rating': rating})\n\n df = pd.DataFrame(restaurants)\n print(df.head())\n <\/code>\n <\/pre>\n5.3 \ub370\uc774\ud130 \uc804\ucc98\ub9ac<\/h3>\n
6. \ubaa8\ub378 \ud6c8\ub828 \ubc0f \uac80\uc99d<\/h2>\n
6.1 \ud6c8\ub828 \ucf54\ub4dc \uc608\uc2dc<\/h3>\n
\n
\n from sklearn.model_selection import train_test_split\n from sklearn.ensemble import RandomForestClassifier\n from sklearn.metrics import accuracy_score\n\n X = df[['feature1', 'feature2', 'feature3']] # \ud559\uc2b5\uc6a9 \ud53c\ucc98\n y = df['target'] # \ud0c0\uac9f \ubcc0\uc218\n\n X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n model = RandomForestClassifier()\n model.fit(X_train, y_train)\n\n y_pred = model.predict(X_test)\n print('Accuracy:', accuracy_score(y_test, y_pred))\n <\/code>\n <\/pre>\n<\/section>\n7. \uacb0\ub860 \ubc0f \ud5a5\ud6c4 \uc5f0\uad6c \ubc29\ud5a5<\/h2>\n