{"id":29927,"date":"2024-10-28T03:18:43","date_gmt":"2024-10-28T03:18:43","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=29927"},"modified":"2024-11-26T06:50:48","modified_gmt":"2024-11-26T06:50:48","slug":"%eb%94%a5%eb%9f%ac%eb%8b%9d-%ed%8c%8c%ec%9d%b4%ed%86%a0%ec%b9%98-%ea%b0%95%ec%a2%8c-lstm-%ea%b5%ac%ec%a1%b0","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/29927\/","title":{"rendered":"\ub525\ub7ec\ub2dd \ud30c\uc774\ud1a0\uce58 \uac15\uc88c, LSTM \uad6c\uc870"},"content":{"rendered":"\n<p>\ud30c\uc774\ud1a0\uce58(Pytorch)\ub97c \ud65c\uc6a9\ud55c \ub525\ub7ec\ub2dd \uac15\uc88c \uc2dc\ub9ac\uc988\uc758 \uc774\ubc88 \uae00\uc5d0\uc11c\ub294 LSTM(Long Short-Term Memory) \ub124\ud2b8\uc6cc\ud06c\uc5d0 \ub300\ud574 \ub2e4\ub904\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. LSTM\uc740 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\ub098 \uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc640 \uac19\uc740 \uc21c\ucc28\uc801 \ub370\uc774\ud130\ub97c \ub2e4\ub8e8\ub294 \ub370 \uac15\ub825\ud55c \uc131\ub2a5\uc744 \ubc1c\ud718\ud558\ub294 \ub525\ub7ec\ub2dd \ubaa8\ub378\uc785\ub2c8\ub2e4. \ud2b9\ud788 \uacfc\uac70\uc758 \uc815\ubcf4\ub97c \uc7a5\uae30\uc801\uc73c\ub85c \uc720\uc9c0\ud558\uba74\uc11c\ub3c4 \ucd5c\uc2e0 \uc815\ubcf4\uc758 \uc911\uc694\uc131\uc744 \uc801\uc808\ud788 \ubc18\uc601\ud560 \uc218 \uc788\uc5b4, \ubcf5\uc7a1\ud55c \ud328\ud134 \uc778\uc2dd\uc744 \uc798 \uc218\ud589\ud569\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ud2b9\uc131 \ub355\ubd84\uc5d0 LSTM\uc740 \ud14d\uc2a4\ud2b8 \uc0dd\uc131, \uc74c\uc131 \uc778\uc2dd, \ubc88\uc5ed, \uc8fc\uc2dd \uac00\uaca9 \uc608\uce21 \ub4f1 \ub2e4\uc591\ud55c \uc751\uc6a9 \ubd84\uc57c\uc5d0\uc11c \ub110\ub9ac \uc0ac\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. LSTM\uc740 RNN(Recurrent Neural Network)\uc758 \ub2e8\uc810\uc744 \uac1c\uc120\ud55c \ubaa8\ub378\ub85c, \uae34 \uc2dc\ud000\uc2a4 \ub370\uc774\ud130\uc5d0\uc11c\ub3c4 \uc548\uc815\uc801\uc73c\ub85c \ud559\uc2b5\uc744 \uc218\ud589\ud560 \uc218 \uc788\ub294 \uac15\ub825\ud55c \ub3c4\uad6c\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">LSTM\uc758 \uae30\ubcf8 \uad6c\uc870<\/h3>\n\n\n\n<p>LSTM\uc740 RNN(Recurrent Neural Network)\uc758 \uc77c\uc885\uc73c\ub85c, \ubc18\ubcf5\uc801\uc778 \uc5f0\uacb0 \uad6c\uc870\ub97c \ud1b5\ud574 \uc21c\ucc28\uc801\uc778 \ub370\uc774\ud130\uc5d0 \ub300\ud55c \ud559\uc2b5\uc744 \uc218\ud589\ud569\ub2c8\ub2e4. \uadf8\ub7ec\ub098 RNN\uc758 \uace0\uc9c8\uc801\uc778 \ubb38\uc81c\uc600\ub358 <strong>\uc7a5\uae30 \uc758\uc874\uc131 \ubb38\uc81c<\/strong>\ub97c \ud574\uacb0\ud558\uae30 \uc704\ud574 \uace0\uc548\ub41c \uac83\uc774 \ubc14\ub85c LSTM\uc785\ub2c8\ub2e4. RNN\uc740 \uae34 \uc2dc\ud000\uc2a4 \ub370\uc774\ud130\uc5d0\uc11c \uc774\uc804 \uc815\ubcf4\ub97c \uc78a\uc5b4\ubc84\ub9ac\ub294 \uacbd\ud5a5\uc774 \uc788\ub294\ub370, LSTM\uc740 \uc774\ub7ec\ud55c \ubb38\uc81c\ub97c \ud574\uacb0\ud558\uae30 \uc704\ud574 \uace0\uc720\ud55c <strong>\uac8c\uc774\ud2b8(Gate)<\/strong> \uad6c\uc870\ub97c \uc0ac\uc6a9\ud569\ub2c8\ub2e4. LSTM\uc740 \ub124\ud2b8\uc6cc\ud06c\uac00 \uc815\ubcf4\ub97c \ub354 \uc798 \uae30\uc5b5\ud558\uac70\ub098 \uc78a\uc744 \uc218 \uc788\ub3c4\ub85d <strong>\uc785\ub825 \uac8c\uc774\ud2b8(Input Gate)<\/strong>, <strong>\ub9dd\uac01 \uac8c\uc774\ud2b8(Forget Gate)<\/strong>, **\ucd9c\ub825 \uac8c\uc774\ud2b8(Output Gate)**\ub77c\ub294 \uc138 \uac00\uc9c0 \uc8fc\uc694 \uac8c\uc774\ud2b8\ub97c \ud1b5\ud574 \uc815\ubcf4\uc758 \ud750\ub984\uc744 \uc81c\uc5b4\ud569\ub2c8\ub2e4.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>\uc785\ub825 \uac8c\uc774\ud2b8<\/strong>: \ud604\uc7ac \uc785\ub825\ub41c \uc815\ubcf4\ub97c \uc5bc\ub9c8\ub098 \ub124\ud2b8\uc6cc\ud06c\uc758 \uc0c1\ud0dc\uc5d0 \ubc18\uc601\ud560\uc9c0 \uacb0\uc815\ud569\ub2c8\ub2e4. \uc774 \uac8c\uc774\ud2b8\ub294 \uc0c8\ub85c\uc6b4 \uc815\ubcf4\uac00 \uc5bc\ub9c8\ub098 \uc911\uc694\ud55c\uc9c0\ub97c \ud310\ub2e8\ud558\uace0, \ub124\ud2b8\uc6cc\ud06c\uc758 \uc0c1\ud0dc\uc5d0 \ubc18\uc601\ud560 \uc815\ub3c4\ub97c \uc870\uc808\ud569\ub2c8\ub2e4.<\/li>\n\n\n\n<li><strong>\ub9dd\uac01 \uac8c\uc774\ud2b8<\/strong>: \uc774\uc804\uc758 \uc815\ubcf4\ub97c \uc5bc\ub9c8\ub098 \uc78a\uc744\uc9c0 \uacb0\uc815\ud558\ub294 \uc5ed\ud560\uc744 \ud569\ub2c8\ub2e4. \uc774 \uac8c\uc774\ud2b8\ub97c \ud1b5\ud574 \ubd88\ud544\uc694\ud55c \uc815\ubcf4\ub294 \uc81c\uac70\ud558\uace0, \uc911\uc694\ud55c \uc815\ubcf4\ub9cc\uc744 \uc720\uc9c0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 LSTM\uc740 \uc7a5\uae30\uc801\uc778 \uc815\ubcf4\uc640 \ucd5c\uc2e0 \uc815\ubcf4\ub97c \uade0\ud615 \uc788\uac8c \uc720\uc9c0\ud569\ub2c8\ub2e4.<\/li>\n\n\n\n<li><strong>\ucd9c\ub825 \uac8c\uc774\ud2b8<\/strong>: \ucd5c\uc885\uc801\uc73c\ub85c \ub2e4\uc74c \ub808\uc774\uc5b4\ub85c \uc804\ub2ec\ud560 \uc815\ubcf4\ub97c \uacb0\uc815\ud569\ub2c8\ub2e4. \uc774 \uac8c\uc774\ud2b8\ub294 \ud604\uc7ac \uc2dc\uc810\uc758 \uc0c1\ud0dc\uc5d0\uc11c \uc5b4\ub5a4 \uc815\ubcf4\ub97c \ucd9c\ub825\ud560\uc9c0 \uc870\uc808\ud558\uba70, \ub2e4\uc74c \ub2e8\uacc4\ub85c \uc804\ub2ec\ud560 \uc815\ubcf4\uc758 \uc591\uc744 \uacb0\uc815\ud569\ub2c8\ub2e4.<\/li>\n<\/ul>\n\n\n\n<p>\uc774\ub7ec\ud55c \uac8c\uc774\ud2b8 \uad6c\uc870 \ub355\ubd84\uc5d0 LSTM\uc740 \ud544\uc694\ud55c \uc815\ubcf4\ub97c \uc624\ub798\ub3c4\ub85d \uae30\uc5b5\ud558\uace0, \ubd88\ud544\uc694\ud55c \uc815\ubcf4\ub294 \ud6a8\uc728\uc801\uc73c\ub85c \uc78a\uc74c\uc73c\ub85c\uc368 \uae34 \uc2dc\ud000\uc2a4\uc5d0\uc11c\ub3c4 \ud6a8\uacfc\uc801\uc778 \ud559\uc2b5\uc744 \ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub294 RNN\uc5d0\uc11c \ubc1c\uc0dd\ud558\ub294 <strong>\uadf8\ub798\ub514\uc5b8\ud2b8 \uc18c\uc2e4(vanishing gradient)<\/strong> \ubb38\uc81c\ub97c \uc644\ud654\ud558\uace0, \uae34 \uc758\uc874\uc131\uc744 \uac00\uc9c4 \ub370\uc774\ud130\uc5d0\uc11c\ub3c4 \ud6a8\uacfc\uc801\uc73c\ub85c \ud559\uc2b5\ud560 \uc218 \uc788\ub3c4\ub85d \ub3d5\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">\ud30c\uc774\ud1a0\uce58\ub85c LSTM \uad6c\ud604\ud558\uae30<\/h3>\n\n\n\n<p>\ud30c\uc774\ud1a0\uce58\uc5d0\uc11c LSTM\uc744 \uad6c\ud604\ud558\ub294 \ubc29\ubc95\uc740 \ud06c\uac8c \ub450 \uac00\uc9c0\uc785\ub2c8\ub2e4. <strong>nn.LSTM \ubaa8\ub4c8<\/strong>\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uacfc <strong>\uc9c1\uc811 LSTM \uc140\uc744 \uc815\uc758\ud558\ub294 \ubc29\ubc95<\/strong>\uc785\ub2c8\ub2e4. <code>nn.LSTM<\/code> \ubaa8\ub4c8\uc740 \uc774\ubbf8 \uc798 \ucd5c\uc801\ud654\ub41c LSTM \uad6c\uc870\ub97c \uc81c\uacf5\ud558\ubbc0\ub85c, \uc774\ub97c \ud65c\uc6a9\ud558\uba74 \uc27d\uac8c LSTM \ub124\ud2b8\uc6cc\ud06c\ub97c \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc5ec\uae30\uc11c\ub294 \uae30\ubcf8\uc801\uc778 <code>nn.LSTM<\/code> \ubaa8\ub4c8\uc744 \ud65c\uc6a9\ud55c \uc608\uc81c\ub97c \ud1b5\ud574 \uac04\ub2e8\ud788 LSTM \ubaa8\ub378\uc744 \uad6c\ud604\ud574\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import torch\nimport torch.nn as nn\nimport torch.optim as optim\n\n# LSTM \ubaa8\ub378 \uc815\uc758\nclass LSTMModel(nn.Module):\n    def __init__(self, input_size, hidden_size, output_size, num_layers=1):\n        super(LSTMModel, self).__init__()\n        self.lstm = nn.LSTM(input_size, hidden_size, num_layers, batch_first=True)\n        self.fc = nn.Linear(hidden_size, output_size)\n    \n    def forward(self, x):\n        out, (h_n, c_n) = self.lstm(x)\n        out = self.fc(out&#91;:, -1, :])\n        return out\n\n# \ud558\uc774\ud37c\ud30c\ub77c\ubbf8\ud130 \uc124\uc815\ninput_size = 10\nhidden_size = 50\noutput_size = 1\nnum_layers = 2\n\n# \ubaa8\ub378, \uc190\uc2e4 \ud568\uc218, \uc635\ud2f0\ub9c8\uc774\uc800 \uc815\uc758\nmodel = LSTMModel(input_size, hidden_size, output_size, num_layers)\ncriterion = nn.MSELoss()\noptimizer = optim.Adam(model.parameters(), lr=0.001)<\/code><\/pre>\n\n\n\n<p>\uc704 \ucf54\ub4dc\uc5d0\uc11c\ub294 \uae30\ubcf8\uc801\uc778 LSTM \ubaa8\ub378\uc744 \uc815\uc758\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. <code>input_size<\/code>, <code>hidden_size<\/code>, <code>output_size<\/code> \ub4f1\uc758 \ud558\uc774\ud37c\ud30c\ub77c\ubbf8\ud130\ub97c \uc124\uc815\ud55c \ub4a4, LSTM \ub808\uc774\uc5b4\uc640 \uc120\ud615 \ub808\uc774\uc5b4\ub97c \uacb0\ud569\ud558\uc5ec \ubaa8\ub378\uc744 \uad6c\uc131\ud588\uc2b5\ub2c8\ub2e4. <code>forward()<\/code> \ud568\uc218\uc5d0\uc11c LSTM\uc758 \ucd9c\ub825\uc744 \ud1b5\ud574 \ucd5c\uc885 \uc608\uce21 \uac12\uc744 \uacc4\uc0b0\ud558\ub3c4\ub85d \ud569\ub2c8\ub2e4. \uc5ec\uae30\uc11c <code>batch_first=True<\/code> \uc635\uc158\uc740 \uc785\ub825 \ud150\uc11c\uc758 \uccab \ubc88\uc9f8 \ucc28\uc6d0\uc774 \ubc30\uce58 \ud06c\uae30\uc784\uc744 \uc758\ubbf8\ud558\uba70, \ubc30\uce58 \ud615\ud0dc\uc758 \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud560 \ub54c \uc720\uc6a9\ud569\ub2c8\ub2e4.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">\ud559\uc2b5 \ubc0f \uc608\uce21<\/h3>\n\n\n\n<p>LSTM \ubaa8\ub378\uc744 \ud559\uc2b5\uc2dc\ud0a4\uae30 \uc704\ud574\uc11c\ub294 \uc21c\ucc28\uc801\uc778 \ub370\uc774\ud130\uac00 \ud544\uc694\ud569\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4 \uc8fc\uc2dd\uc758 \uac00\uaca9 \uc608\uce21, \ub0a0\uc528 \ub370\uc774\ud130 \ubd84\uc11d, \ud14d\uc2a4\ud2b8 \uc0dd\uc131\uacfc \uac19\uc740 \ubd84\uc57c\uc5d0\uc11c LSTM\uc758 \uc131\ub2a5\uc744 \ud14c\uc2a4\ud2b8\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. LSTM\uc740 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\uc5d0\uc11c \uacfc\uac70\uc758 \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \ubbf8\ub798\ub97c \uc608\uce21\ud558\ub294 \ub370 \uc801\ud569\ud558\uba70, \uc774\ub294 \uc2dc\uacc4\uc5f4 \ud2b9\uc131\uc0c1 \ub370\uc774\ud130\uac00 \uc2dc\uac04\uc5d0 \ub530\ub77c \ubcc0\ud654\ud558\ub294 \ud328\ud134\uc744 \ubc18\uc601\ud558\uae30 \ub54c\ubb38\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># \uc608\uc2dc \ub370\uc774\ud130 (\uc2dc\uacc4\uc5f4 \ub370\uc774\ud130)\ndata = torch.randn(100, 10, input_size)  # 100\uac1c\uc758 \uc2dc\ud000\uc2a4, \uac01 \uc2dc\ud000\uc2a4 \uae38\uc774 10, \uc785\ub825 \ud06c\uae30 input_size\nlabels = torch.randn(100, output_size)   # 100\uac1c\uc758 \ub808\uc774\ube14\n\n# \ud559\uc2b5 \ub8e8\ud504\nepochs = 100\nfor epoch in range(epochs):\n    model.train()\n    optimizer.zero_grad()\n    outputs = model(data)\n    loss = criterion(outputs, labels)\n    loss.backward()\n    optimizer.step()\n    \n    if (epoch+1) % 10 == 0:\n        print(f'Epoch &#91;{epoch+1}\/{epochs}], Loss: {loss.item():.4f}')<\/code><\/pre>\n\n\n\n<p>\uc774 \ucf54\ub4dc\ub294 \uc608\uc2dc \ub370\uc774\ud130\ub97c \uc774\uc6a9\ud574 \ubaa8\ub378\uc744 \ud559\uc2b5\ud558\ub294 \uac04\ub2e8\ud55c \uacfc\uc815\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \ud559\uc2b5 \ub370\uc774\ud130\uc640 \ub808\uc774\ube14\uc744 \ud1b5\ud574 \uc190\uc2e4 \ud568\uc218\ub97c \uacc4\uc0b0\ud558\uace0, \uc5ed\uc804\ud30c\ub97c \ud1b5\ud574 \uac00\uc911\uce58\ub97c \uc5c5\ub370\uc774\ud2b8\ud569\ub2c8\ub2e4. \uc190\uc2e4 \ud568\uc218\ub85c\ub294 <code>MSELoss<\/code>\ub97c \uc0ac\uc6a9\ud558\uba70, \uc774\ub294 \ud68c\uadc0 \ubb38\uc81c\uc5d0\uc11c \uc790\uc8fc \uc0ac\uc6a9\ub418\ub294 \uc190\uc2e4 \ud568\uc218\uc785\ub2c8\ub2e4. \uc635\ud2f0\ub9c8\uc774\uc800\ub85c\ub294 <code>Adam<\/code>\uc744 \uc0ac\uc6a9\ud558\uc5ec, \ud6a8\uc728\uc801\uc778 \ud559\uc2b5\uc744 \ub3c4\ubaa8\ud569\ub2c8\ub2e4.<\/p>\n\n\n\n<p>LSTM \ubaa8\ub378\uc740 \ub370\uc774\ud130\uc758 \uc2dc\ud000\uc2a4 \uae38\uc774\uc5d0 \ub530\ub77c \ucd9c\ub825\uc774 \ub2ec\ub77c\uc9c8 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \uc8fc\uc2dd \uac00\uaca9 \uc608\uce21\uc5d0\uc11c \ud2b9\uc815 \uae30\uac04 \ub3d9\uc548\uc758 \ub370\uc774\ud130\ub97c \uc785\ub825\uc73c\ub85c \uc0ac\uc6a9\ud558\uba74, \ud574\ub2f9 \uae30\uac04\uc758 \uac00\uaca9 \ubcc0\ub3d9\uc744 \ubc18\uc601\ud55c \uc608\uce21\uc744 \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\uc640 \uac19\uc740 \uc2dc\ud000\uc2a4 \uc608\uce21\uc740 \uc785\ub825 \ub370\uc774\ud130\uc758 \uc2dc\uac04\uc801 \ud750\ub984\uc744 \uc774\ud574\ud558\uace0 \ubbf8\ub798\ub97c \uc608\uce21\ud558\ub294 \ub370 \uc911\uc694\ud55c \uc5ed\ud560\uc744 \ud569\ub2c8\ub2e4.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">LSTM\uc758 \ud65c\uc6a9 \ubd84\uc57c<\/h3>\n\n\n\n<p>LSTM\uc740 \uc2dc\uacc4\uc5f4 \uc608\uce21, \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP), \uc74c\uc131 \uc778\uc2dd, \ub3d9\uc791 \uc778\uc2dd \ub4f1 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0\uc11c \ud65c\uc6a9\ub429\ub2c8\ub2e4. \ud2b9\ud788 \ud14d\uc2a4\ud2b8\uc758 \uc758\ubbf8\ub97c \uc774\ud574\ud558\uac70\ub098, \uc8fc\uc2dd \uc2dc\uc7a5\uc758 \ubcc0\ub3d9\uc131\uc744 \uc608\uce21\ud558\ub294 \ub370 \uc720\uc6a9\ud569\ub2c8\ub2e4. \uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc5d0\uc11c\ub294 LSTM\uc744 \uc0ac\uc6a9\ud558\uc5ec \ubb38\uc7a5\uc758 \ubb38\ub9e5\uc744 \uc774\ud574\ud558\uace0, \uc774\ub97c \ubc14\ud0d5\uc73c\ub85c \ubc88\uc5ed\ud558\uac70\ub098 \ud14d\uc2a4\ud2b8\ub97c \uc0dd\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc74c\uc131 \uc778\uc2dd\uc5d0\uc11c\ub294 \uc5f0\uc18d\uc801\uc778 \uc74c\uc131 \uc2e0\ud638\ub97c \uc774\ud574\ud558\uace0, \uc774\ub97c \ud14d\uc2a4\ud2b8\ub85c \ubcc0\ud658\ud558\ub294 \ub370 \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \ub610\ud55c LSTM\uc740 \uc0ac\ub78c\uc758 \ub3d9\uc791\uc744 \uc778\uc2dd\ud558\uac70\ub098 \uc608\uce21\ud558\ub294 \ub370\uc5d0\ub3c4 \uc0ac\uc6a9\ub420 \uc218 \uc788\uc5b4, \uc608\ub97c \ub4e4\uc5b4 \ub3d9\uc791 \uc778\uc2dd\uc744 \ud1b5\ud574 \ube44\ub514\uc624\uc5d0\uc11c \ud2b9\uc815 \ud65c\ub3d9\uc744 \ud0d0\uc9c0\ud558\ub294 \ub370 \uc720\uc6a9\ud569\ub2c8\ub2e4.<\/p>\n\n\n\n<p>\ud30c\uc774\ud1a0\uce58\uc758 <code>nn.LSTM<\/code>\uc744 \uc0ac\uc6a9\ud558\uba74 \ube44\uad50\uc801 \uac04\ub2e8\ud558\uac8c LSTM \ubaa8\ub378\uc744 \uad6c\ud604\ud560 \uc218 \uc788\uc73c\uba70, \uc774\ub97c \ud1b5\ud574 \ubcf5\uc7a1\ud55c \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\ub3c4 \ud6a8\uacfc\uc801\uc73c\ub85c \ucc98\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788 \uc5ec\ub7ec \uacc4\uce35\uc758 LSTM\uc744 \uc313\uc544 <strong>\uc2ec\uce35 LSTM(Deep LSTM)<\/strong> \uad6c\uc870\ub97c \ub9cc\ub4e4\uba74, \ub354 \ubcf5\uc7a1\ud558\uace0 \ub2e4\uc591\ud55c \ud328\ud134\uc744 \ud559\uc2b5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uc2ec\uce35 \uad6c\uc870\ub294 \uc2dc\ud000\uc2a4 \ub370\uc774\ud130\uc758 \uc800\ucc28\uc6d0 \ud45c\ud604\ubd80\ud130 \uace0\ucc28\uc6d0 \ud45c\ud604\uae4c\uc9c0 \ub2e8\uacc4\uc801\uc73c\ub85c \ud559\uc2b5\ud568\uc73c\ub85c\uc368, \ub370\uc774\ud130\uc758 \uc911\uc694\ud55c \ud2b9\uc9d5\uc744 \ud6a8\uacfc\uc801\uc73c\ub85c \ucd94\ucd9c\ud560 \uc218 \uc788\uac8c \ud569\ub2c8\ub2e4.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">\ub9c8\ubb34\ub9ac<\/h3>\n\n\n\n<p>\uc774\ubc88 \uae00\uc5d0\uc11c\ub294 LSTM\uc758 \uae30\ubcf8 \uac1c\ub150\uacfc \ud30c\uc774\ud1a0\uce58\ub97c \uc774\uc6a9\ud55c \uac04\ub2e8\ud55c \uad6c\ud604 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uc558\uc2b5\ub2c8\ub2e4. LSTM\uc740 \uc7a5\uae30 \uc758\uc874\uc131\uc744 \ucc98\ub9ac\ud558\ub294 \ub370 \ub9e4\uc6b0 \uc720\uc6a9\ud55c \ub3c4\uad6c\uc774\uba70, \uc774\ub97c \ub2e4\uc591\ud55c \ub525\ub7ec\ub2dd \uc751\uc6a9 \ubd84\uc57c\uc5d0 \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788 \uac8c\uc774\ud2b8 \uad6c\uc870\ub97c \ud1b5\ud574 \uc7a5\uae30 \ubc0f \ub2e8\uae30 \uae30\uc5b5\uc744 \ud6a8\uc728\uc801\uc73c\ub85c \uad00\ub9ac\ud558\uba70, \uae34 \uc2dc\ud000\uc2a4 \ub370\uc774\ud130\uc5d0\uc11c\ub3c4 \uc131\ub2a5\uc774 \uc88b\uc2b5\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ud2b9\uc131 \ub355\ubd84\uc5d0 LSTM\uc740 \ub9ce\uc740 \ub525\ub7ec\ub2dd \uc5f0\uad6c \ubc0f \uc751\uc6a9 \ubd84\uc57c\uc5d0\uc11c \ub9e4\uc6b0 \uc911\uc694\ud55c \uc5ed\ud560\uc744 \ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n<p>\ub2e4\uc74c \uae00\uc5d0\uc11c\ub294 GRU(Gated Recurrent Unit)\uc640 \uac19\uc740 \ub2e4\ub978 \uc21c\ud658 \uc2e0\uacbd\ub9dd \uad6c\uc870\uc5d0 \ub300\ud574 \uc0b4\ud3b4\ubcfc \uc608\uc815\uc785\ub2c8\ub2e4. GRU\ub294 LSTM\uc758 \ub2e8\uc21c\ud654\ub41c \ubc84\uc804\uc73c\ub85c, \ube44\uc2b7\ud55c \uc131\ub2a5\uc744 \uc720\uc9c0\ud558\uba74\uc11c\ub3c4 \uacc4\uc0b0 \ubcf5\uc7a1\ub3c4\uac00 \ub0ae\uc544 \ub9ce\uc740 \uacbd\uc6b0\uc5d0\uc11c LSTM\uc744 \ub300\uccb4\ud560 \uc218 \uc788\ub294 \uc720\uc6a9\ud55c \ubaa8\ub378\uc785\ub2c8\ub2e4. GRU\uc640 LSTM\uc758 \ucc28\uc774\uc810, \uadf8\ub9ac\uace0 \uac01 \ubaa8\ub378\uc758 \uc7a5\ub2e8\uc810\uc5d0 \ub300\ud574\uc11c\ub3c4 \uc2ec\ub3c4 \uc788\uac8c \ub2e4\ub8f0 \uc608\uc815\uc774\ub2c8 \ub9ce\uc740 \uad00\uc2ec \ubd80\ud0c1\ub4dc\ub9bd\ub2c8\ub2e4.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ud30c\uc774\ud1a0\uce58(Pytorch)\ub97c \ud65c\uc6a9\ud55c \ub525\ub7ec\ub2dd \uac15\uc88c \uc2dc\ub9ac\uc988\uc758 \uc774\ubc88 \uae00\uc5d0\uc11c\ub294 LSTM(Long Short-Term Memory) \ub124\ud2b8\uc6cc\ud06c\uc5d0 \ub300\ud574 \ub2e4\ub904\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. LSTM\uc740 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\ub098 \uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc640 \uac19\uc740 \uc21c\ucc28\uc801 \ub370\uc774\ud130\ub97c \ub2e4\ub8e8\ub294 \ub370 \uac15\ub825\ud55c \uc131\ub2a5\uc744 \ubc1c\ud718\ud558\ub294 \ub525\ub7ec\ub2dd \ubaa8\ub378\uc785\ub2c8\ub2e4. \ud2b9\ud788 \uacfc\uac70\uc758 \uc815\ubcf4\ub97c \uc7a5\uae30\uc801\uc73c\ub85c \uc720\uc9c0\ud558\uba74\uc11c\ub3c4 \ucd5c\uc2e0 \uc815\ubcf4\uc758 \uc911\uc694\uc131\uc744 \uc801\uc808\ud788 \ubc18\uc601\ud560 \uc218 \uc788\uc5b4, \ubcf5\uc7a1\ud55c \ud328\ud134 \uc778\uc2dd\uc744 \uc798 \uc218\ud589\ud569\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ud2b9\uc131 \ub355\ubd84\uc5d0 LSTM\uc740 \ud14d\uc2a4\ud2b8 \uc0dd\uc131, \uc74c\uc131 \uc778\uc2dd, \ubc88\uc5ed, \uc8fc\uc2dd &hellip; <a href=\"https:\/\/atmokpo.com\/w\/29927\/\" class=\"more-link\">\ub354 \ubcf4\uae30<span class=\"screen-reader-text\"> &#8220;\ub525\ub7ec\ub2dd \ud30c\uc774\ud1a0\uce58 \uac15\uc88c, LSTM \uad6c\uc870&#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":[33],"tags":[],"class_list":["post-29927","post","type-post","status-publish","format-standard","hentry","category-33"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\ub525\ub7ec\ub2dd \ud30c\uc774\ud1a0\uce58 \uac15\uc88c, LSTM \uad6c\uc870 - \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\/29927\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\ub525\ub7ec\ub2dd \ud30c\uc774\ud1a0\uce58 \uac15\uc88c, LSTM \uad6c\uc870 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"\ud30c\uc774\ud1a0\uce58(Pytorch)\ub97c \ud65c\uc6a9\ud55c \ub525\ub7ec\ub2dd \uac15\uc88c \uc2dc\ub9ac\uc988\uc758 \uc774\ubc88 \uae00\uc5d0\uc11c\ub294 LSTM(Long Short-Term Memory) \ub124\ud2b8\uc6cc\ud06c\uc5d0 \ub300\ud574 \ub2e4\ub904\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. 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LSTM\uc740 \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\ub098 \uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc640 \uac19\uc740 \uc21c\ucc28\uc801 \ub370\uc774\ud130\ub97c \ub2e4\ub8e8\ub294 \ub370 \uac15\ub825\ud55c \uc131\ub2a5\uc744 \ubc1c\ud718\ud558\ub294 \ub525\ub7ec\ub2dd \ubaa8\ub378\uc785\ub2c8\ub2e4. \ud2b9\ud788 \uacfc\uac70\uc758 \uc815\ubcf4\ub97c \uc7a5\uae30\uc801\uc73c\ub85c \uc720\uc9c0\ud558\uba74\uc11c\ub3c4 \ucd5c\uc2e0 \uc815\ubcf4\uc758 \uc911\uc694\uc131\uc744 \uc801\uc808\ud788 \ubc18\uc601\ud560 \uc218 \uc788\uc5b4, \ubcf5\uc7a1\ud55c \ud328\ud134 \uc778\uc2dd\uc744 \uc798 \uc218\ud589\ud569\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ud2b9\uc131 \ub355\ubd84\uc5d0 LSTM\uc740 \ud14d\uc2a4\ud2b8 \uc0dd\uc131, \uc74c\uc131 \uc778\uc2dd, \ubc88\uc5ed, \uc8fc\uc2dd &hellip; \ub354 \ubcf4\uae30 \"\ub525\ub7ec\ub2dd \ud30c\uc774\ud1a0\uce58 \uac15\uc88c, LSTM 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