\uc8fc\uc2dd \uc2dc\uc7a5\uc5d0\uc11c\uc758 \uac70\ub798\ub294 \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \ud55c \uc758\uc0ac\uacb0\uc815\uc774 \ud575\uc2ec\uc785\ub2c8\ub2e4. \ucd5c\uadfc \uba87 \ub144\uac04 \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd \uae30\uc220\uc740 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529 \ubd84\uc57c\uc5d0 \ud070 \uc601\ud5a5\uc744 \ubbf8\uce58\uace0 \uc788\uc73c\uba70, \ud22c\uc790\uc790\ub4e4\uc740 \uc774\ub7ec\ud55c \uae30\uc220\uc744 \ud65c\uc6a9\ud558\uc5ec \uc218\uc775\uc744 \uadf9\ub300\ud654\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \uc5e5\uae00-\uadf8\ub808\uc778\uc800 2\ub2e8\uacc4 \ubc29\ubc95\uc744 \uc911\uc810\uc801\uc73c\ub85c \ub2e4\ub8e8\uba74\uc11c, \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd\uc744 \ud1b5\ud55c \ud2b8\ub808\uc774\ub529 \uc804\ub7b5\uc744 \uad6c\ud604\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/p>\n
\uba38\uc2e0\ub7ec\ub2dd\uc740 \ucef4\ud4e8\ud130\uac00 \uc8fc\uc5b4\uc9c4 \ub370\uc774\ud130\ub97c \ud1b5\ud574 \ud559\uc2b5\ud558\uace0 \uc608\uce21\ud558\ub3c4\ub85d \ud558\ub294 \uae30\uc220\uc785\ub2c8\ub2e4. \ubc18\uba74, \ub525\ub7ec\ub2dd\uc740 \uba38\uc2e0\ub7ec\ub2dd\uc758 \ud55c \ubd84\uc57c\ub85c, \uc778\uacf5 \uc2e0\uacbd\ub9dd\uc744 \uae30\ubc18\uc73c\ub85c \ud55c \ubcf5\uc7a1\ud55c \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\uc5ec \ub354 \ub192\uc740 \uc815\ud655\ub3c4\ub97c \ucd94\uad6c\ud569\ub2c8\ub2e4. \ub458 \ub2e4 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc5d0 \uc801\ud569\ud558\uc9c0\ub9cc, \uac01\uac01\uc758 \uc7a5\ub2e8\uc810\uc774 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
\ub525\ub7ec\ub2dd\uc740 \uc218\ub9ce\uc740 \uacc4\uce35(layer)\uc73c\ub85c \uad6c\uc131\ub41c \uc778\uacf5 \uc2e0\uacbd\ub9dd\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc73c\ub85c, \ube44\uc815\ud615 \ub370\uc774\ud130(\uc608: \uc774\ubbf8\uc9c0, \ud14d\uc2a4\ud2b8)\ub97c \ucc98\ub9ac\ud558\ub294 \ub370 \uac15\uc810\uc744 \uac00\uc9d1\ub2c8\ub2e4. \uc5ec\uae30\uc5d0 \uc0ac\uc6a9\ub418\ub294 \uc8fc\uc694 \uc54c\uace0\ub9ac\uc998 \uc911 \ud558\ub098\uac00 \ud569\uc131\uacf1 \uc2e0\uacbd\ub9dd(Convolutional Neural Networks, CNN)\uc774\uace0, \uc2dc\ud000\uc2a4 \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud558\ub294 \ub370 \uc0ac\uc6a9\ub418\ub294 \uac83\uc774 \uc21c\ud658 \uc2e0\uacbd\ub9dd(Recurrent Neural Networks, RNN)\uc785\ub2c8\ub2e4.<\/p>\n
\uc5e5\uae00-\uadf8\ub808\uc778\uc800 \ubc29\ubc95\uc740 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\ub97c \ubd84\uc11d\ud558\uc5ec \ud2b9\ud788 \uae08\uc735 \ub370\uc774\ud130\ub97c \uc608\uce21\ud558\ub294 \ub370 \uc801\ud569\ud55c \ubc29\ubc95\ub860\uc785\ub2c8\ub2e4. \uc8fc\uc2dd \uc2dc\uc7a5\uc758 \ube44\uc120\ud615\uc131\uacfc \ubcf5\uc7a1\uc131\uc744 \uace0\ub824\ud560 \ub54c, \uc774 \ubc29\ubc95\ub860\uc740 \ub9e4\uc6b0 \uc720\uc6a9\ud558\uac8c \ud65c\uc6a9\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \ubc29\ubc95\uc758 \ub450 \ub2e8\uacc4\ub294 \uc544\ub798\uc640 \uac19\uc2b5\ub2c8\ub2e4.<\/p>\n
\uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\ub294 \uc2dc\uac04\uc774 \uc9c0\ub0a8\uc5d0 \ub530\ub77c \uc218\uc9d1\ub41c \ub370\uc774\ud130\ub85c, \uc2dc\uac04\uc5d0 \ub530\ub978 \ud328\ud134, \ud2b8\ub80c\ub4dc \ubc0f \uc8fc\uae30\uc131\uc744 \ubd84\uc11d\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc5e5\uae00-\uadf8\ub808\uc778\uc800 \ubc29\ubc95\uc5d0\uc11c\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 \uc808\ucc28\ub97c \ud1b5\ud574 \ub370\uc774\ud130\ub97c \ubd84\ud574\ud569\ub2c8\ub2e4.<\/p>\n
\ubd84\ud574\ub41c \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \uba38\uc2e0\ub7ec\ub2dd\uc774\ub098 \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud558\uc5ec \uc608\uce21 \ubaa8\ub378\uc744 \uad6c\ucd95\ud569\ub2c8\ub2e4. \uae30\ubcf8\uc801\uc778 \uc54c\uace0\ub9ac\uc998\uc5d0\uc11c\ub294 ARIMA(model), LSTM, GRU \ub4f1\uc774 \uc0ac\uc6a9\ub418\uba70, \uc774\ub97c \ud1b5\ud574 \uc131\ub2a5\uc744 \uadf9\ub300\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
LSTM\uc740 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130 \uc608\uce21\uc5d0 \ub9e4\uc6b0 \uc720\uc6a9\ud55c \ub525\ub7ec\ub2dd \ubaa8\ub378\ub85c, \uc7a5\uae30 \uc758\uc874\uc131\uc744 \ud559\uc2b5\ud560 \uc218 \uc788\ub294 \ub2a5\ub825\uc774 \ub6f0\uc5b4\ub0a9\ub2c8\ub2e4. \uae30\ubcf8\uc801\uc778 LSTM \ub124\ud2b8\uc6cc\ud06c\ub294 \uc544\ub798\uc640 \uac19\uc740 \uad6c\uc870\ub85c \uad6c\uc131\ub429\ub2c8\ub2e4.<\/p>\n
\nimport numpy as np\nimport pandas as pd\nfrom keras.models import Sequential\nfrom keras.layers import LSTM, Dense, Dropout\n\n# \ub370\uc774\ud130 \uc900\ube44\ndata = pd.read_csv(\"stock_prices.csv\")\nX, y = prepare_data(data)\n\n# LSTM \ubaa8\ub378 \uad6c\ucd95\nmodel = Sequential()\nmodel.add(LSTM(50, return_sequences=True, input_shape=(X.shape[1], X.shape[2])))\nmodel.add(Dropout(0.2))\nmodel.add(LSTM(50, return_sequences=False))\nmodel.add(Dropout(0.2))\nmodel.add(Dense(1))\n\n# \ubaa8\ub378 \ucef4\ud30c\uc77c \ubc0f \ud6c8\ub828\nmodel.compile(optimizer='adam', loss='mean_squared_error')\nmodel.fit(X, y, epochs=100, batch_size=32)\n<\/pre>\n<\/div>\n3. \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529 \uc804\ub7b5 \uad6c\ud604<\/h2>\n
3.1 \ub370\uc774\ud130 \uc218\uc9d1 \ubc0f \uc804\ucc98\ub9ac<\/h3>\n
\ub370\uc774\ud130 \uc218\uc9d1\uc740 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \uccab \ubc88\uc9f8 \ub2e8\uacc4\ub85c, \uc815\ud655\ud558\uace0 \uc2e0\ub8b0\ud560 \uc218 \uc788\ub294 \ub370\uc774\ud130\ub97c \ud655\ubcf4\ud574\uc57c \ud569\ub2c8\ub2e4. Yahoo Finance, Alpha Vantage, Quandl\uacfc \uac19\uc740 \ub370\uc774\ud130 \uc81c\uacf5 \uc11c\ube44\uc2a4\ub97c \ud1b5\ud574 \uc8fc\uac00 \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
3.1.1 \ub370\uc774\ud130 \uc218\uc9d1 \uc608\uc2dc<\/h4>\n
\n\nimport yfinance as yf\n\n# \ub370\uc774\ud130 \ub2e4\uc6b4\ub85c\ub4dc\nticker = \"AAPL\"\ndata = yf.download(ticker, start=\"2020-01-01\", end=\"2023-01-01\")\ndata.to_csv(\"AAPL_stock_data.csv\")\n<\/pre>\n<\/div>\n3.2 \ud2b9\uc131 \uc120\ud0dd \ubc0f \ubaa8\ub378 \ud559\uc2b5<\/h3>\n
\ud2b9\uc131 \uc120\ud0dd\uc740 \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \uc88c\uc6b0\ud558\ub294 \uc911\uc694\ud55c \uacfc\uc815\uc785\ub2c8\ub2e4. \uacfc\uac70 \ub370\uc774\ud130\uc5d0\uc11c \uac00\uaca9, \uac70\ub798\ub7c9, \uae30\uc220 \uc9c0\ud45c \ub4f1\uc744 \ud2b9\uc131\uc73c\ub85c \ucd94\ucd9c\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub97c \ubc14\ud0d5\uc73c\ub85c \uba38\uc2e0\ub7ec\ub2dd \ubaa8\ub378\uc744 \ud559\uc2b5\uc2dc\ud0a4\uace0 \uac80\uc99d\ud558\ub294 \uacfc\uc815\uc774 \ud544\uc694\ud569\ub2c8\ub2e4.<\/p>\n
3.2.1 \uae30\uc220\uc801 \uc9c0\ud45c \uc608\uc2dc<\/h4>\n
\n\n# \uc774\ub3d9 \ud3c9\uade0 \uacc4\uc0b0\ndata['SMA_50'] = data['Close'].rolling(window=50).mean()\ndata['EMA_50'] = data['Close'].ewm(span=50, adjust=False).mean()\n<\/pre>\n<\/div>\n3.3 \ubaa8\ub378 \ud3c9\uac00<\/h3>\n
\ubaa8\ub378 \ud3c9\uac00 \ub2e8\uacc4\uc5d0\uc11c\ub294 \ud6c8\ub828 \ub370\uc774\ud130\uc640 \ud14c\uc2a4\ud2b8 \ub370\uc774\ud130\ub97c \ubd84\ub9ac\ud558\uc5ec \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \uce21\uc815\ud569\ub2c8\ub2e4. RMSE(Root Mean Square Error), MSE(Mean Square Error) \ub4f1\uc758 \uc9c0\ud45c\ub97c \ud65c\uc6a9\ud558\uc5ec \uc608\uce21\uc758 \uc815\ud655\uc131\uc744 \ud655\uc778\ud569\ub2c8\ub2e4.<\/p>\n
4. \uacb0\ub860<\/h2>\n
\uc5e5\uae00-\uadf8\ub808\uc778\uc800 2\ub2e8\uacc4 \ubc29\ubc95\uc740 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\ub97c \ud6a8\uacfc\uc801\uc73c\ub85c \ubd84\uc11d\ud558\uace0 \uc608\uce21\ud560 \uc218 \uc788\ub294 \uc720\uc6a9\ud55c \ubc29\ubc95\ub860\uc785\ub2c8\ub2e4. \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd \uae30\ubc95\uc744 \ud65c\uc6a9\ud558\uc5ec \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529 \uc804\ub7b5\uc744 \uad6c\ud604\ud568\uc73c\ub85c\uc368, \ud22c\uc790\uc790\ub294 \ub370\uc774\ud130 \uae30\ubc18\uc758 \uc804\ub7b5\uc801 \uacb0\uc815\uc744 \ub0b4\ub9b4 \uc218 \uc788\ub294 \uae30\ud68c\ub97c \uc5bb\uac8c \ub429\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd\uc744 \ud1b5\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \uae30\ubcf8 \uac1c\ub150\uc744 \uc18c\uac1c\ud558\uc600\uc73c\uba70, \uc5e5\uae00-\uadf8\ub808\uc778\uc800 \ubc29\ubc95\uc744 \uad6c\uccb4\uc801\uc73c\ub85c \uc124\uba85\ud588\uc2b5\ub2c8\ub2e4. \uc55e\uc73c\ub85c\ub3c4 \uc9c0\uc18d\uc801\uc778 \ud559\uc2b5\uacfc \uacbd\ud5d8\uc744 \ud1b5\ud574 \ud2b8\ub808\uc774\ub529 \uc804\ub7b5\uc744 \ubc1c\uc804\uc2dc\ud0ac \uc218 \uc788\uae30\ub97c \ubc14\ub78d\ub2c8\ub2e4.<\/p>\n
<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"