{"id":31409,"date":"2024-10-28T12:01:49","date_gmt":"2024-10-28T12:01:49","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=31409"},"modified":"2024-11-26T06:45:14","modified_gmt":"2024-11-26T06:45:14","slug":"%eb%94%a5%eb%9f%ac%eb%8b%9d%ea%b3%bc-%eb%a8%b8%ec%8b%a0%eb%9f%ac%eb%8b%9d%ec%9d%84-%ed%99%9c%ec%9a%a9%ed%95%9c-%ec%9e%90%eb%8f%99%eb%a7%a4%eb%a7%a4-%ed%8a%b8%eb%9e%9c%ec%8a%a4%ed%8f%ac%eb%a8%b8","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/31409\/","title":{"rendered":"\ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4, \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ubaa8\ub378\uc744 \uc774\uc6a9\ud55c \uc2dc\uacc4\uc5f4 \uc608\uce21 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \uae30\ubc18\uc758 \uc2dc\uacc4\uc5f4 \uc608\uce21 \ubaa8\ub378\uc744 \ud65c\uc6a9\ud55c \ub9e4\ub9e4 \uc804\ub7b5."},"content":{"rendered":"

\ucd5c\uadfc \uba87 \ub144 \uac04 \uc554\ud638\ud654\ud3d0 \uc2dc\uc7a5\uc774 \uae09\uc131\uc7a5\ud558\uba74\uc11c, \ube44\ud2b8\ucf54\uc778\uc744 \ud3ec\ud568\ud55c \ub2e4\uc591\ud55c \uc554\ud638\ud654\ud3d0\uc5d0 \ub300\ud55c \ud22c\uc790 \ubc29\ubc95\uc774 \uc8fc\ubaa9\ubc1b\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uadf8 \uc911\uc5d0\uc11c\ub3c4 \ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd \uae30\uc220\uc744 \ud65c\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc774 \ud070 \uc778\uae30\ub97c \ub04c\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \ud2b9\ud788 \ud2b8\ub79c\uc2a4\ud3ec\uba38(transfomer)<\/strong> \ubaa8\ub378\uc744 \ud65c\uc6a9\ud558\uc5ec \ube44\ud2b8\ucf54\uc778 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\ub97c \uc608\uce21\ud558\uace0, \uc774\ub97c \ubc14\ud0d5\uc73c\ub85c \ub9e4\ub9e4 \uc804\ub7b5\uc744 \uc138\uc6b0\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \ub2e4\ub8e8\uc5b4 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n

1. \ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc758 \uae30\ubcf8 \uac1c\ub150<\/h2>\n

\ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc740 \uc778\uacf5\uc9c0\ub2a5\uc758 \ud55c \ubd84\uc57c\ub85c, \ub370\uc774\ud130\ub85c\ubd80\ud130 \ud328\ud134\uc744 \ud559\uc2b5\ud558\uc5ec \uc608\uce21\uc774\ub098 \ubd84\ub958\ub97c \uc218\ud589\ud558\ub294 \uc54c\uace0\ub9ac\uc998\ub4e4\uc785\ub2c8\ub2e4. \uba38\uc2e0\ub7ec\ub2dd\uc740 \uc8fc\ub85c \uc8fc\uc5b4\uc9c4 \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \ubaa8\ub378\uc744 \ud559\uc2b5\uc2dc\ucf1c \uacb0\uacfc\ub97c \uc608\uce21\ud558\ub294 \uae30\uc220\uc744 \ud3ec\ud568\ud558\uba70, \uc774 \uc911 \ub525\ub7ec\ub2dd\uc740 \uc778\uacf5\uc2e0\uacbd\ub9dd\uc744 \ud65c\uc6a9\ud558\uc5ec \ub354 \ubcf5\uc7a1\ud558\uace0 \ube44\uc120\ud615\uc801\uc778 \ubb38\uc81c\ub97c \ud574\uacb0\ud560 \uc218 \uc788\ub294 \ub2a5\ub825\uc744 \uc9c0\ub2c8\uace0 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n

2. \uc2dc\uacc4\uc5f4 \uc608\uce21\uc758 \uc911\uc694\uc131<\/h2>\n

\ube44\ud2b8\ucf54\uc778\uacfc \uac19\uc740 \uc554\ud638\ud654\ud3d0\uc758 \uac00\uaca9\uc740 \uc2dc\uac04\uc5d0 \ub530\ub77c \ubcc0\ud654\ud558\ub294 \ubcf5\uc7a1\ud55c \ub370\uc774\ud130\ub97c \ud3ec\ud568\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ub370\uc774\ud130\ub294 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\ub85c, \uacfc\uac70\uc758 \ub370\uc774\ud130\ub85c\ubd80\ud130 \ubbf8\ub798\ub97c \uc608\uce21\ud558\ub294 \ub370 \uc911\uc694\ud55c \uc5ed\ud560\uc744 \ud569\ub2c8\ub2e4. \ubd88\uc548\uc815\ud55c \uc2dc\uc7a5\uc5d0\uc11c \ub9e4\ub9e4 \uacb0\uc815\uc744 \ub0b4\ub9ac\uae30 \uc704\ud574\uc11c\ub294 \ud6a8\uc728\uc801\uc778 \uc608\uce21 \ubaa8\ub378\uc774 \ud544\uc694\ud569\ub2c8\ub2e4.<\/p>\n

3. \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ubaa8\ub378 \uac1c\uc694<\/h2>\n

\ud2b8\ub79c\uc2a4\ud3ec\uba38 \ubaa8\ub378\uc740 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c \ucc98\uc74c \ub3c4\uc785\ub41c \ubaa8\ub378\ub85c, \uc804\uccb4 \uc785\ub825 \uc2dc\ud000\uc2a4\ub97c \ub3d9\uc2dc\uc5d0 \ucc98\ub9ac\ud560 \uc218 \uc788\ub294 \uc7a5\uc810\uc774 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub294 \uacfc\uac70\uc758 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\ub97c \ud65c\uc6a9\ud558\uc5ec \ubbf8\ub798\uc758 \uac12\uc744 \uc608\uce21\ud558\ub294 \ub370\uc5d0\ub3c4 \uc801\ud569\ud569\ub2c8\ub2e4. \ud2b8\ub79c\uc2a4\ud3ec\uba38\uc758 \uc8fc\uc694 \uad6c\uc131\uc694\uc18c\ub294 \uc790\uae30 \uc8fc\uc758(attention)<\/strong> \uba54\ucee4\ub2c8\uc998\uacfc \ub2e4\uce35 \uc778\ucf54\ub354-\ub514\ucf54\ub354 \uad6c\uc870<\/strong>\uc785\ub2c8\ub2e4.<\/p>\n

3.1 \uc790\uae30 \uc8fc\uc758 \uba54\ucee4\ub2c8\uc998<\/h3>\n

\uc790\uae30 \uc8fc\uc758 \uba54\ucee4\ub2c8\uc998\uc740 \uc785\ub825 \ub370\uc774\ud130\uc758 \uac01 \ubd80\ubd84\uc774 \uc11c\ub85c \uc5b4\ub5bb\uac8c \uad00\uacc4\ub418\ub294\uc9c0\ub97c \uacc4\uc0b0\ud560 \uc218 \uc788\uac8c \ud574\uc90d\ub2c8\ub2e4. \uc774 \uae30\uc220\uc744 \ud65c\uc6a9\ud558\uba74, \uac01 \uc785\ub825 \uac12\uc774 \ub2e4\ub978 \uc785\ub825 \uac12\uc5d0 \uc5bc\ub9c8\ub098 \uc601\ud5a5\uc744 \ubbf8\uce58\ub294\uc9c0\ub97c \ub3d9\uc801\uc73c\ub85c \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n

3.2 \uc778\ucf54\ub354-\ub514\ucf54\ub354 \uad6c\uc870<\/h3>\n

\uc778\ucf54\ub354\ub294 \uc785\ub825 \ub370\uc774\ud130\ub97c \ubc1b\uc544\uc11c \ub0b4\uc7ac\uc801\uc778 \uc758\ubbf8\ub97c \uc555\ucd95\ud558\uc5ec \ub2e4\uc74c \ub2e8\uacc4\ub85c \uc804\ub2ec\ud569\ub2c8\ub2e4. \ub514\ucf54\ub354\ub294 \uc774 \ub0b4\uc7ac\uc801\uc778 \uc758\ubbf8\ub97c \ubc14\ud0d5\uc73c\ub85c \uc608\uce21 \uac12\uc744 \uc0dd\uc131\ud569\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uad6c\uc870\ub294 \ubcf5\uc7a1\ud55c \uc2dc\uacc4\uc5f4 \uc608\uce21\uc5d0\uc11c\ub3c4 \uc720\uc6a9\ud558\uac8c \uc0ac\uc6a9\ub429\ub2c8\ub2e4.<\/p>\n

4. \ube44\ud2b8\ucf54\uc778 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130 \uc900\ube44<\/h2>\n

\ubaa8\ub378\uc744 \ud6c8\ub828\uc2dc\ud0a4\uae30 \uc704\ud574 \ube44\ud2b8\ucf54\uc778\uc758 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud574\uc57c \ud569\ub2c8\ub2e4. \uc5ec\uae30\uc11c\ub294 \ud30c\uc774\uc36c\uc758 pandas<\/code> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec \ub370\uc774\ud130\ub97c \uc804\ucc98\ub9ac\ud558\ub294 \uacfc\uc815\uc744 \uc18c\uac1c\ud569\ub2c8\ub2e4.<\/p>\n

import pandas as pd\nimport numpy as np\n\n# \ub370\uc774\ud130 \ub85c\ub4dc\ndata = pd.read_csv('bitcoin_price.csv')  # \ube44\ud2b8\ucf54\uc778 \uac00\uaca9 \ub370\uc774\ud130\ub97c \ud3ec\ud568\ud55c CSV \ud30c\uc77c \uacbd\ub85c\n\n# \ub0a0\uc9dc\ub97c datetime \ud615\uc2dd\uc73c\ub85c \ubcc0\ud658\ndata['Date'] = pd.to_datetime(data['Date'])\n\n# \ud544\uc694\ud55c \uc5f4 \uc120\ud0dd\ndata = data[['Date', 'Close']]\n\n# \uc778\ub371\uc2a4\ub97c \ub0a0\uc9dc\ub85c \uc124\uc815\ndata.set_index('Date', inplace=True)\n\n# \uacb0\uce21\uac12 \ucc98\ub9ac\ndata = data.fillna(method='ffill')\n\n# \ub370\uc774\ud130 \ud655\uc778\nprint(data.head())<\/code><\/pre>\n
5. \ud2b8\ub79c\uc2a4\ud3ec\uba38 \uc2dc\uacc4\uc5f4 \uc608\uce21 \ubaa8\ub378 \uad6c\ucd95<\/h2>\n
\uc774\uc81c \uc900\ube44\ub41c \ube44\ud2b8\ucf54\uc778 \uac00\uaca9 \ub370\uc774\ud130\ub85c \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\uaca0\uc2b5\ub2c8\ub2e4. \uc774\ub97c \uc704\ud574 TensorFlow<\/strong>\uc640 Keras<\/strong> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud560 \uac83\uc785\ub2c8\ub2e4.<\/p>\n
5.1 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ubaa8\ub378 \uc815\uc758<\/h3>\n
import tensorflow as tf\nfrom tensorflow import keras\n\ndef create_transformer_model(input_shape, num_heads, ff_dim):\n    inputs = keras.Input(shape=input_shape)\n    attention = keras.layers.MultiHeadAttention(num_heads=num_heads, key_dim=input_shape[-1])(inputs, inputs)\n    x = keras.layers.Add()([inputs, attention])  # Skip connection\n    x = keras.layers.LayerNormalization()(x)\n    x = keras.layers.Dense(ff_dim, activation='relu')(x)  # Feed Forward Network\n    x = keras.layers.Dense(input_shape[-1])(x)\n    x = keras.layers.Add()([inputs, x])  # Skip connection\n    x = keras.layers.LayerNormalization()(x)\n    \n    # Output layer\n    outputs = keras.layers.Dense(1)(x)\n    \n    model = keras.Model(inputs=inputs, outputs=outputs)\n    return model\n\n# \ubaa8\ub378 \uc0dd\uc131\nmodel = create_transformer_model(input_shape=(30, 1), num_heads=4, ff_dim=32)\nmodel.compile(optimizer='adam', loss='mean_squared_error')\n\n# \ubaa8\ub378 \uc694\uc57d\nmodel.summary()<\/code><\/pre>\n
5.2 \ub370\uc774\ud130 \uc804\ucc98\ub9ac \ubc0f \ubaa8\ub378 \ud6c8\ub828<\/h3>\n
\ud2b8\ub79c\uc2a4\ud3ec\uba38 \ubaa8\ub378\uc744 \ud6c8\ub828\uc2dc\ud0a4\uae30 \uc704\ud574 \ub370\uc774\ud130\ub97c \uc77c\uc815\ud55c \uae38\uc774\uc758 \uc2dc\ud000\uc2a4\ub85c \ub098\ub204\uc5b4\uc57c \ud569\ub2c8\ub2e4.<\/p>\n
def create_sequences(data, seq_length):\n    sequences = []\n    labels = []\n    for i in range(len(data) - seq_length):\n        sequences.append(data[i:i+seq_length])\n        labels.append(data[i+seq_length])\n    return np.array(sequences), np.array(labels)\n\n# \uc2dc\uacc4\uc5f4 \uae38\uc774 \uc124\uc815\nSEQ_LENGTH = 30\n\n# \uc2dc\ud000\uc2a4 \uc0dd\uc131\nsequences, labels = create_sequences(data['Close'].values, SEQ_LENGTH)\n\n# \ud6c8\ub828 \uc138\ud2b8\uc640 \uac80\uc99d \uc138\ud2b8\ub85c \ubd84\ub9ac\nsplit_idx = int(len(sequences) * 0.8)\nX_train, X_val = sequences[:split_idx], sequences[split_idx:]\ny_train, y_val = labels[:split_idx], labels[split_idx:]\n\n# \ubaa8\ub378 \ud6c8\ub828\nmodel.fit(X_train, y_train, validation_data=(X_val, y_val), epochs=50, batch_size=32)<\/code><\/pre>\n
6. \ub9e4\ub9e4 \uc804\ub7b5 \uad6c\ucd95<\/h2>\n
\ubaa8\ub378\uc774 \ud6c8\ub828\ub41c \ud6c4, \ud604\uc2e4\uc801\uc778 \ub9e4\ub9e4 \uc804\ub7b5\uc744 \uc218\ub9bd\ud574\uc57c \ud569\ub2c8\ub2e4. \uae30\ubcf8\uc801\uc778 \ub9e4\ub9e4 \uc804\ub7b5\uc740 \ub2e4\uc74c\uacfc \uac19\uc740 \uae30\ubcf8 \uaddc\uce59\uc744 \uae30\ubc18\uc73c\ub85c \ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
6.1 \ub9e4\uc218\/\ub9e4\ub3c4 \uc2e0\ud638 \uc0dd\uc131<\/h3>\n
def generate_signals(predictions, threshold=0.01):\n    signals = []\n    for i in range(1, len(predictions)):\n        if predictions[i] > predictions[i - 1] * (1 + threshold):\n            signals.append(1)  # Buy\n        elif predictions[i] < predictions[i - 1] * (1 - threshold):\n            signals.append(-1)  # Sell\n        else:\n            signals.append(0)  # Hold\n    return signals\n\n# \uc608\uce21 \uc0dd\uc131\npredictions = model.predict(X_val)\nsignals = generate_signals(predictions.flatten())\n\n# \uc2e0\ud638 \ud655\uc778\nprint(signals[-10:])<\/code><\/pre>\n
7. \uacb0\uacfc \ud3c9\uac00<\/h2>\n
\ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud3c9\uac00\ud558\uae30 \uc704\ud574 \ub2e4\uc591\ud55c \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \uc815\ud655\ub3c4<\/strong>, \uc815\ubc00\ub3c4<\/strong>, \uc7ac\ud604\uc728<\/strong> \ub4f1\uc744 \uacc4\uc0b0\ud558\uc5ec \ubaa8\ub378\uc758 \uc608\uce21\ub825\uc744 \uce21\uc815\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub610\ud55c, \uc2e4\uc81c \ub9e4\ub9e4\ub97c \ud1b5\ud55c \uc218\uc775\ub960\uc744 \ud3c9\uac00\ud558\uc5ec \uc804\ub7b5\uc758 \uc720\ud6a8\uc131\uc744 \uac80\uc99d\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
7.1 \uc131\ub2a5 \uc9c0\ud45c \uacc4\uc0b0<\/h3>\n
def calculate_performance(signals, actual_prices):\n    portfolio = 10000  # \ucd08\uae30 \ud22c\uc790\uae08\uc561\n    for i in range(len(signals)):\n        if signals[i] == 1:  # Buy\n            portfolio *= (actual_prices[i+1] \/ actual_prices[i])\n        elif signals[i] == -1:  # Sell\n            portfolio *= (actual_prices[i] \/ actual_prices[i+1])\n    return portfolio\n\n# \uc131\uacfc \uacc4\uc0b0\nfinal_portfolio_value = calculate_performance(signals, data['Close'].values[-len(signals):])\nprint(f'\ucd5c\uc885 \ud3ec\ud2b8\ud3f4\ub9ac\uc624 \uac00\uce58: {final_portfolio_value}') \/\/<\/code><\/pre>\n
8. \uacb0\ub860<\/h2>\n
\ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \ube44\ud2b8\ucf54\uc778 \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc740 \ubcf5\uc7a1\ud55c \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud558\uc5ec \uc608\uce21\uc744 \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ubaa8\ub378\uc740 \uacfc\uac70 \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \ubbf8\ub798 \uac00\uaca9\uc744 \uc608\uce21\ud558\ub294 \ub370 \ub9e4\uc6b0 \ud6a8\uacfc\uc801\uc778 \ub3c4\uad6c\uc785\ub2c8\ub2e4. \uadf8\ub7ec\ub098 \uc2dc\uc7a5\uc758 \ud2b9\uc131\uc0c1 \uc5b4\ub5a0\ud55c \ubaa8\ub378\ub3c4 \uc644\ubcbd\ud55c \uc608\uce21\uc744 \ubcf4\uc7a5\ud560 \uc218\ub294 \uc5c6\uc73c\uba70, \ud56d\uc0c1 \ub9ac\uc2a4\ud06c\ub97c \uac10\uc218\ud574\uc57c \ud569\ub2c8\ub2e4. \ub530\ub77c\uc11c \uc774\ub7ec\ud55c \ubaa8\ub378\uc744 \ud65c\uc6a9\ud560 \ub54c\ub294 \ub2e4\uc591\ud55c \uc704\ud5d8 \uad00\ub9ac \uae30\ubc95\uacfc \ud568\uaed8 \uc885\ud569\uc801\uc778 \uc804\ub7b5\uc744 \uad6c\uc131\ud558\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4.<\/p>\n
\uc774 \uae00\uc5d0\uc11c \uc124\uba85\ud55c \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ubaa8\ub378\uc744 \ud65c\uc6a9\ud55c \ube44\ud2b8\ucf54\uc778 \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc740 \uc55e\uc73c\ub85c\ub3c4 \ub354\uc6b1 \ubc1c\uc804\ud560 \uac83\uc785\ub2c8\ub2e4. \ub370\uc774\ud130 \uc218\uc9d1 \ubc0f \ucc98\ub9ac, \ubaa8\ub378 \ud6c8\ub828 \ubc0f \ud3c9\uac00 \uacfc\uc815\uc744 \ud1b5\ud574 \ub2e4\uc591\ud55c \uc804\ub7b5\uc744 \ubaa8\uc0c9\ud558\uc5ec \uc790\uc2e0\ub9cc\uc758 \ud22c\uc790 \ubc29\uc2dd\uc744 \uad6c\ucd95\ud574 \ub098\uac00\uae38 \ubc14\ub78d\ub2c8\ub2e4.<\/p>\n","protected":false},"excerpt":{"rendered":"
\ucd5c\uadfc \uba87 \ub144 \uac04 \uc554\ud638\ud654\ud3d0 \uc2dc\uc7a5\uc774 \uae09\uc131\uc7a5\ud558\uba74\uc11c, \ube44\ud2b8\ucf54\uc778\uc744 \ud3ec\ud568\ud55c \ub2e4\uc591\ud55c \uc554\ud638\ud654\ud3d0\uc5d0 \ub300\ud55c \ud22c\uc790 \ubc29\ubc95\uc774 \uc8fc\ubaa9\ubc1b\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uadf8 \uc911\uc5d0\uc11c\ub3c4 \ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd \uae30\uc220\uc744 \ud65c\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc774 \ud070 \uc778\uae30\ub97c \ub04c\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \ud2b9\ud788 \ud2b8\ub79c\uc2a4\ud3ec\uba38(transfomer) \ubaa8\ub378\uc744 \ud65c\uc6a9\ud558\uc5ec \ube44\ud2b8\ucf54\uc778 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\ub97c \uc608\uce21\ud558\uace0, \uc774\ub97c \ubc14\ud0d5\uc73c\ub85c \ub9e4\ub9e4 \uc804\ub7b5\uc744 \uc138\uc6b0\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \ub2e4\ub8e8\uc5b4 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4. 1. \ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc758 \uae30\ubcf8 \uac1c\ub150 \ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc740 \uc778\uacf5\uc9c0\ub2a5\uc758 … \ub354 \ubcf4\uae30 “\ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4, \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ubaa8\ub378\uc744 \uc774\uc6a9\ud55c \uc2dc\uacc4\uc5f4 \uc608\uce21  \ud2b8\ub79c\uc2a4\ud3ec\uba38 \uae30\ubc18\uc758 \uc2dc\uacc4\uc5f4 \uc608\uce21 \ubaa8\ub378\uc744 \ud65c\uc6a9\ud55c \ub9e4\ub9e4 \uc804\ub7b5.”<\/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":[29],"tags":[],"class_list":["post-31409","post","type-post","status-publish","format-standard","hentry","category-29"],"yoast_head":"\n\ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4, \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ubaa8\ub378\uc744 \uc774\uc6a9\ud55c \uc2dc\uacc4\uc5f4 \uc608\uce21 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \uae30\ubc18\uc758 \uc2dc\uacc4\uc5f4 \uc608\uce21 \ubaa8\ub378\uc744 \ud65c\uc6a9\ud55c \ub9e4\ub9e4 \uc804\ub7b5. - 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