{"id":25263,"date":"2024-10-26T09:53:26","date_gmt":"2024-10-26T09:53:26","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=25263"},"modified":"2024-11-26T08:02:21","modified_gmt":"2024-11-26T08:02:21","slug":"07-09-%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-%ec%bc%80%eb%9d%bc%ec%8a%a4%ec%9d%98-%ed%95%a8%ec%88%98%ed%98%95-api-keras-func","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/25263\/","title":{"rendered":"07-09 \ub525 \ub7ec\ub2dd\uc744 \uc774\uc6a9\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac, \ucf00\ub77c\uc2a4\uc758 \ud568\uc218\ud615 API (Keras Functional API)"},"content":{"rendered":"<div>\n<p>\ub525 \ub7ec\ub2dd\uc740 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c \uac15\ub825\ud55c \ub3c4\uad6c\ub85c \uc790\ub9ac\uc7a1\uace0 \uc788\uc73c\uba70, \ub300\uaddc\ubaa8 \ub370\uc774\ud130\uc640 \ubcf5\uc7a1\ud55c \ubaa8\ub378\uc744 \ucc98\ub9ac\ud560 \uc218 \uc788\ub294 \ub2a5\ub825\uc744 \uac00\uc9c0\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 Keras\uc758 \ud568\uc218\ud615 API\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub525 \ub7ec\ub2dd\uc744 \ud1b5\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\ub294 \ubc29\ubc95\uc744 \ub2e4\ub8f0 \uac83\uc785\ub2c8\ub2e4. Keras\ub294 TensorFlow\uc5d0\uc11c \uc81c\uacf5\ud558\ub294 \uace0\uc218\uc900\uc758 \uc2e0\uacbd\ub9dd API\ub85c, \ud568\uc218\ud615 API\ub97c \ud1b5\ud574 \ubcf5\uc7a1\ud55c \ubaa8\ub378 \uc544\ud0a4\ud14d\ucc98\ub97c \uc27d\uac8c \uad6c\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>\uc790\uc5f0\uc5b4 \ucc98\ub9ac\ub780?<\/h2>\n<p>\uc790\uc5f0\uc5b4 \ucc98\ub9ac\ub294 \ucef4\ud4e8\ud130\uac00 \uc778\uac04\uc758 \uc5b8\uc5b4\ub97c \uc774\ud574\ud558\uace0 \ud574\uc11d\ud560 \uc218 \uc788\ub3c4\ub85d \ub3d5\ub294 \uae30\uc220 \ubd84\uc57c\uc785\ub2c8\ub2e4. \uc774 \uacfc\uc815\uc5d0\ub294 \ud14d\uc2a4\ud2b8\uc758 \uc758\ubbf8\ub97c \ud30c\uc545\ud558\uace0, \ubb38\uc7a5 \uac04\uc758 \uad00\uacc4\ub97c \uc774\ud574\ud558\uba70, \uac10\uc815\uc744 \ubd84\uc11d\ud558\ub294 \ub4f1\uc758 \ub2e4\uc591\ud55c \uc791\uc5c5\uc774 \ud3ec\ud568\ub429\ub2c8\ub2e4. NLP\ub294 \ucc57\ubd07, \uae30\uacc4 \ubc88\uc5ed, \uac10\uc131 \ubd84\uc11d \ub4f1 \ub2e4\uc591\ud55c \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc5d0\uc11c \ud65c\uc6a9\ub429\ub2c8\ub2e4.<\/p>\n<h3>\uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc758 \uc8fc\uc694 \uc791\uc5c5<\/h3>\n<ul>\n<li><strong>\ud1a0\ud070\ud654(Tokenization):<\/strong> \ud14d\uc2a4\ud2b8\ub97c \ub2e8\uc5b4, \ubb38\uc7a5 \ub610\ub294 \uad6c\ubb38\uc73c\ub85c \ubd84\ub9ac\ud558\ub294 \uacfc\uc815\uc785\ub2c8\ub2e4.<\/li>\n<li><strong>\ubd88\uc6a9\uc5b4 \uc81c\uac70(Stop Word Removal):<\/strong> \uc758\ubbf8 \uc5c6\ub294 \ub2e8\uc5b4(\uc608: &#8220;\uc740&#8221;, &#8220;\uc774&#8221;, &#8220;\uc5d0\uc11c&#8221;)\ub97c \uc81c\uac70\ud558\uc5ec \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud5a5\uc0c1\uc2dc\ud0a4\ub294 \uc791\uc5c5\uc785\ub2c8\ub2e4.<\/li>\n<li><strong>\uc5b4\uac04 \ucd94\ucd9c(Stemming) \ubc0f \uc6d0\ud615 \ubcf5\uc6d0(Lemmatization):<\/strong> \ub2e8\uc5b4\uc758 \ud615\ud0dc\ub97c \uc77c\uad00\ub418\uac8c \ub9cc\ub4e4\uc5b4 \ubaa8\ub378\uc758 \uc785\ub825\uc744 \uc815\uaddc\ud654\ud558\ub294 \uacfc\uc815\uc785\ub2c8\ub2e4.<\/li>\n<li><strong>\uac10\uc131 \ubd84\uc11d(Sentiment Analysis):<\/strong> \uc8fc\uc5b4\uc9c4 \ubb38\uc7a5\uc758 \uac10\uc815\uc744 \ubd84\uc11d\ud558\ub294 \uc791\uc5c5\uc785\ub2c8\ub2e4.<\/li>\n<li><strong>\uae30\uacc4 \ubc88\uc5ed(Machine Translation):<\/strong> \ud55c \uc5b8\uc5b4\ub85c \uc791\uc131\ub41c \ud14d\uc2a4\ud2b8\ub97c \ub2e4\ub978 \uc5b8\uc5b4\ub85c \ubcc0\ud658\ud558\ub294 \uacfc\uc815\uc785\ub2c8\ub2e4.<\/li>\n<\/ul>\n<h2>\ub525 \ub7ec\ub2dd\uc758 \ubc1c\uc804\uacfc NLP<\/h2>\n<p>\ub525 \ub7ec\ub2dd\uc740 \uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc758 \ubc1c\uc804\uc744 \ud06c\uac8c \uc774\ub04c\uc5c8\uc2b5\ub2c8\ub2e4. \uc804\ud1b5\uc801\uc778 \uba38\uc2e0\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998\uc740 \ub300\uaddc\ubaa8 \ub370\uc774\ud130\uc14b\uc5d0\uc11c \uc131\ub2a5\uc774 \uc800\ud558\ub418\ub294 \uacbd\ud5a5\uc774 \uc788\uc5c8\uc73c\ub098, \ub525 \ub7ec\ub2dd\uc740 \ud48d\ubd80\ud55c \ud45c\ud604\ub825\uc744 \ud1b5\ud574 \uc774\ub7ec\ud55c \ubb38\uc81c\ub97c \ud574\uacb0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, \ucd5c\uadfc\uc758 Transformer \uc544\ud0a4\ud14d\ucc98\ub294 NLP \ubd84\uc57c\uc5d0\uc11c \ud601\uc2e0\uc801\uc778 \uc131\uacfc\ub97c \ubcf4\uc5ec\uc8fc\uace0 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<h3>Transformer\uc640 BERT<\/h3>\n<p>Transformer \ubaa8\ub378\uc740 Attention \uba54\ucee4\ub2c8\uc998\uc744 \uae30\ubc18\uc73c\ub85c \ud558\uc5ec, \ubb38\uc7a5 \ub0b4\uc758 \ub2e8\uc5b4 \uac04\uc758 \uad00\uacc4\ub97c \ud6a8\uacfc\uc801\uc73c\ub85c \ud559\uc2b5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. BERT(Bidirectional Encoder Representations from Transformers)\ub294 Transformer \ubaa8\ub378\uc758 \uace0\ub3c4\ud654\ub41c \ud615\ud0dc\ub85c, \uc591\ubc29\ud5a5 \ucee8\ud14d\uc2a4\ud2b8\ub97c \uc774\ud574\ud558\ub294 \ub370 \uac15\ub825\ud55c \uc131\ub2a5\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ubaa8\ub378\ub4e4\uc740 \uc5ec\ub7ec NLP \uc791\uc5c5\uc5d0\uc11c \uc0c8\ub85c\uc6b4 \uae30\uc900\uc744 \uc138\uc6b0\uace0 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>Keras\uc758 \ud568\uc218\ud615 API \uc18c\uac1c<\/h2>\n<p>Keras\uc758 \ud568\uc218\ud615 API\ub294 \uc720\uc5f0\ud558\uace0 \uc9c1\uad00\uc801\uc778 \ubc29\ubc95\uc73c\ub85c \ubcf5\uc7a1\ud55c \uc2e0\uacbd\ub9dd \uc544\ud0a4\ud14d\ucc98\ub97c \uad6c\uc131\ud558\ub294 \ub370 \ub3c4\uc6c0\uc774 \ub429\ub2c8\ub2e4. \uae30\ubcf8\uc801\uc73c\ub85c Keras\ub294 \uc21c\ucc28\uc801 \ubaa8\ub378\uc744 \uc27d\uac8c \uad6c\ud604\ud560 \uc218 \uc788\uc9c0\ub9cc, \ub354 \ubcf5\uc7a1\ud55c \uad6c\uc870(\uc608:<strong> \ub2e4\uc911 \uc785\ub825\/\ub2e4\uc911 \ucd9c\ub825 \ubaa8\ub378, \ubd84\uae30 \ubaa8\ub378<\/strong>)\ub97c \ub9cc\ub4e4\uace0\uc790 \ud560 \ub54c \ud568\uc218\ud615 API\uac00 \ud544\uc694\ud569\ub2c8\ub2e4.<\/p>\n<h3>\ud568\uc218\ud615 API\uc758 \ud2b9\uc9d5<\/h3>\n<ul>\n<li><strong>\uc720\uc5f0\uc131:<\/strong> \ub2e4\uc591\ud55c \uad6c\uc870\uc758 \ubaa8\ub378\uc744 \uc27d\uac8c \uc124\uacc4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<li><strong>\ubaa8\ub4c8\uc131:<\/strong> \uac01 \ub808\uc774\uc5b4\ub97c \ud568\uc218\ucc98\ub7fc \ub2e4\ub8f0 \uc218 \uc788\uc5b4 \ucf54\ub4dc\uac00 \uac04\uacb0\ud574\uc9d1\ub2c8\ub2e4.<\/li>\n<li><strong>\ub2e4\uc591\ud55c \ubaa8\ub378 \uad6c\uc131:<\/strong> \uc5ec\ub7ec \uac1c\uc758 \uc785\ub825\uacfc \ucd9c\ub825\uc774 \uc788\ub294 \ubcf5\uc7a1\ud55c \uad6c\uc870\ub97c \ud615\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<\/ul>\n<h2>\ucf00\ub77c\uc2a4 \ud568\uc218\ud615 API\ub85c \ubaa8\ub378 \uad6c\ucd95\ud558\uae30<\/h2>\n<p>\uc774\uc81c Keras\uc758 \ud568\uc218\ud615 API\ub97c \uc774\uc6a9\ud558\uc5ec \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\ub294 \ubc29\ubc95\uc744 \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \uc608\uc2dc\ub85c \uc0ac\uc6a9\ud560 \ub370\uc774\ud130\uc14b\uc740 IMDB \uc601\ud654 \ub9ac\ubdf0 \ub370\uc774\ud130\uc14b\uc785\ub2c8\ub2e4. \uc774 \ub370\uc774\ud130\uc14b\uc740 \uae0d\uc815\uc801\uc778 \ub9ac\ubdf0\uc640 \ubd80\uc815\uc801\uc778 \ub9ac\ubdf0\ub85c \uad6c\uc131\ub418\uc5b4 \uc788\uc73c\uba70, \uc774\ub97c \ud1b5\ud574 \uac10\uc131 \ubd84\uc11d \ubaa8\ub378\uc744 \ub9cc\ub4e4\uc5b4 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n<h3>1. \ub77c\uc774\ube0c\ub7ec\ub9ac \uc784\ud3ec\ud2b8 \ubc0f \ub370\uc774\ud130 \uc900\ube44<\/h3>\n<p>\ubaa8\ub378\uc744 \uad6c\ucd95\ud558\uae30\uc5d0 \uc55e\uc11c \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc784\ud3ec\ud2b8\ud558\uace0, IMDB \ub370\uc774\ud130\uc14b\uc744 \ub2e4\uc6b4\ub85c\ub4dc \ubc0f \uc900\ube44\ud569\ub2c8\ub2e4.<\/p>\n<pre><code>import numpy as np\nimport pandas as pd\nfrom keras.datasets import imdb\nfrom keras.preprocessing.sequence import pad_sequences\nfrom keras.models import Model\nfrom keras.layers import Input, Embedding, LSTM, Dense, GlobalMaxPooling1D\nfrom keras.utils import to_categorical\n<\/code><\/pre>\n<p>\ub370\uc774\ud130\uc14b\uc744 \uc900\ube44\ud558\uae30 \uc704\ud574 \ub2e4\uc74c\uacfc \uac19\uc774 \uc21c\uc11c\ub97c \uc9c4\ud589\ud569\ub2c8\ub2e4.<\/p>\n<pre><code># IMDB \ub370\uc774\ud130\uc14b \ub85c\ub4dc\nnum_words = 10000\n(x_train, y_train), (x_test, y_test) = imdb.load_data(num_words=num_words)\n\n# \uc2dc\ud000\uc2a4 \ud328\ub529\nmaxlen = 100\nx_train = pad_sequences(x_train, maxlen=maxlen)\nx_test = pad_sequences(x_test, maxlen=maxlen)\n<\/code><\/pre>\n<h3>2. \ubaa8\ub378 \uc124\uacc4<\/h3>\n<p>\uc774\uc81c Keras \ud568\uc218\ud615 API\ub97c \uc0ac\uc6a9\ud558\uc5ec LSTM \uae30\ubc18\uc758 \uac10\uc131 \ubd84\uc11d \ubaa8\ub378\uc744 \uc124\uacc4\ud569\ub2c8\ub2e4. \uc785\ub825 \ub808\uc774\uc5b4, \uc784\ubca0\ub529 \ub808\uc774\uc5b4, LSTM \ub808\uc774\uc5b4, \uadf8\ub9ac\uace0 \ucd9c\ub825 \ub808\uc774\uc5b4\ub85c \uad6c\uc131\ub41c \uac04\ub2e8\ud55c \ubaa8\ub378\uc744 \ub9cc\ub4e4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n<pre><code># Input Layer\ninputs = Input(shape=(maxlen,))\n\n# Embedding Layer\nembedding = Embedding(input_dim=num_words, output_dim=128)(inputs)\n\n# LSTM Layer\nlstm = LSTM(100, return_sequences=True)(embedding)\n# Global Max Pooling Layer\npooling = GlobalMaxPooling1D()(lstm)\n\n# Output Layer\noutputs = Dense(1, activation='sigmoid')(pooling)\n\n# Model Definition\nmodel = Model(inputs, outputs)\nmodel.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n<\/code><\/pre>\n<h3>3. \ubaa8\ub378 \ud6c8\ub828<\/h3>\n<p>\ubaa8\ub378 \ud6c8\ub828\uc740 \ub2e4\uc74c\uacfc \uac19\uc774 \uc9c4\ud589\ub429\ub2c8\ub2e4. \ud6c8\ub828 \ub370\uc774\ud130\uc640 \uac80\uc99d \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub378\uc744 \ud6c8\ub828\uc2dc\ud0a4\uace0, \uc5d0\ud3ec\ud06c \uc218\uc5d0 \ub530\ub77c \ud5a5\uc0c1\ub418\ub294 \uc131\ub2a5\uc744 \ud655\uc778\ud569\ub2c8\ub2e4.<\/p>\n<pre><code>history = model.fit(x_train, y_train, epochs=5, batch_size=64, validation_split=0.2)\n<\/code><\/pre>\n<h3>4. \ubaa8\ub378 \ud3c9\uac00<\/h3>\n<p>\ud6c8\ub828\ub41c \ubaa8\ub378\uc744 \ud14c\uc2a4\ud2b8 \ub370\uc774\ud130\uc14b\uc5d0 \ub300\ud574 \ud3c9\uac00\ud569\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 \ubaa8\ub378\uc758 \uc815\ud655\ub3c4\ub97c \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<pre><code>test_loss, test_accuracy = model.evaluate(x_test, y_test)\nprint('Test Accuracy: {:.2f}%'.format(test_accuracy * 100))\n<\/code><\/pre>\n<h2>\uacb0\ub860<\/h2>\n<p>\uc774\ubc88 \ud3ec\uc2a4\ud2b8\uc5d0\uc11c\ub294 Keras\uc758 \ud568\uc218\ud615 API\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub525 \ub7ec\ub2dd \uae30\ubc18\uc758 \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\ub294 \ubc29\ubc95\uc744 \uc0b4\ud3b4\ubcf4\uc558\uc2b5\ub2c8\ub2e4. \uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc758 \uc5ec\ub7ec \uc791\uc5c5\uc744 \ub525 \ub7ec\ub2dd\uc744 \ud1b5\ud574 \ud574\uacb0\ud558\uba70, Keras\uc758 \uc720\uc5f0\ud55c API \ub355\ubd84\uc5d0 \ubcf5\uc7a1\ud55c \ubaa8\ub378\uc744 \uac04\ub2e8\ud558\uac8c \uc124\uacc4\ud560 \uc218 \uc788\uc74c\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc55e\uc73c\ub85c\ub3c4 \ub354\uc6b1 \ubc1c\uc804\ud558\ub294 \uc790\uc5f0\uc5b4 \ucc98\ub9ac \uae30\uc220\uacfc \ub3c4\uad6c\ub4e4\uc744 \ud65c\uc6a9\ud558\uc5ec \ub2e4\uc591\ud55c \ubb38\uc81c\ub97c \ud574\uacb0\ud558\ub294 \ub370 \uae30\uc5ec\ud560 \uc218 \uc788\uae30\ub97c \uae30\ub300\ud569\ub2c8\ub2e4.<\/p>\n<h3>\ucc38\uace0 \ubb38\ud5cc<\/h3>\n<ul>\n<li>Goodfellow, I., Bengio, Y., &amp; Courville, A. (2016). Deep Learning. MIT Press.<\/li>\n<li>Karras, T., Laine, S., &amp; Aila, T. (2019). A Style-Based Generator Architecture for Generative Adversarial Networks.<\/li>\n<li>Vaswani, A., Shard, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, \u0141., et al. (2017). Attention is All You Need.<\/li>\n<\/ul>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>\ub525 \ub7ec\ub2dd\uc740 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ubd84\uc57c\uc5d0\uc11c \uac15\ub825\ud55c \ub3c4\uad6c\ub85c \uc790\ub9ac\uc7a1\uace0 \uc788\uc73c\uba70, \ub300\uaddc\ubaa8 \ub370\uc774\ud130\uc640 \ubcf5\uc7a1\ud55c \ubaa8\ub378\uc744 \ucc98\ub9ac\ud560 \uc218 \uc788\ub294 \ub2a5\ub825\uc744 \uac00\uc9c0\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 Keras\uc758 \ud568\uc218\ud615 API\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub525 \ub7ec\ub2dd\uc744 \ud1b5\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\ub294 \ubc29\ubc95\uc744 \ub2e4\ub8f0 \uac83\uc785\ub2c8\ub2e4. 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