\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc815\ud655\ub3c4 - \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\/29690\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc815\ud655\ub3c4 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"\ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \ud5c8\uae45\ud398\uc774\uc2a4\uc758 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ud0dc\uc2a4\ud06c\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud558\uace0, \ubaa8\ub378\uc758 \uc815\ud655\ub3c4\ub97c \ud3c9\uac00\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \ub2e4\ub8f0 \uac83\uc785\ub2c8\ub2e4. \ud5c8\uae45\ud398\uc774\uc2a4\ub294 \ub2e4\uc591\ud55c \uc0ac\uc804 \ud559\uc2b5(pre-trained) \ubaa8\ub378\uc744 \uc81c\uacf5\ud558\uc5ec NLP \uc791\uc5c5\uc5d0\uc11c \uc27d\uac8c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. 1. \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38\ub780? \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \ub2e4\uc591\ud55c \ucd5c\uc2e0 NLP \ubaa8\ub378\uc744 \uc81c\uacf5\ud558\ub294 Python \ub77c\uc774\ube0c\ub7ec\ub9ac\uc785\ub2c8\ub2e4. \ube44\uc9c0\ub3c4 \ud559\uc2b5, \uc9c0\ub3c4 \ud559\uc2b5\uc744 \ud1b5\ud574 \ubaa8\ub378\uc744 \ud6c8\ub828\uc2dc\ud0ac \uc218 \uc788\uc73c\uba70, \ud2b9\ud788 BERT, … \ub354 \ubcf4\uae30 "\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc815\ud655\ub3c4"\" \/>\n<meta property=\"og:url\" content=\"https:\/\/atmokpo.com\/w\/29690\/\" \/>\n<meta property=\"og:site_name\" content=\"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"article:published_time\" content=\"2024-10-28T01:56:06+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-11-26T06:51:43+00:00\" \/>\n<meta name=\"author\" content=\"root\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@bebubo4\" \/>\n<meta name=\"twitter:site\" content=\"@bebubo4\" \/>\n<meta name=\"twitter:label1\" content=\"\uae00\uc4f4\uc774\" \/>\n\t<meta name=\"twitter:data1\" content=\"root\" \/>\n\t<meta name=\"twitter:label2\" content=\"\uc608\uc0c1 \ub418\ub294 \ud310\ub3c5 \uc2dc\uac04\" \/>\n\t<meta name=\"twitter:data2\" content=\"1\ubd84\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/atmokpo.com\/w\/29690\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/atmokpo.com\/w\/29690\/\"},\"author\":{\"name\":\"root\",\"@id\":\"https:\/\/atmokpo.com\/w\/#\/schema\/person\/91b6b3b138fbba0efb4ae64b1abd81d7\"},\"headline\":\"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc815\ud655\ub3c4\",\"datePublished\":\"2024-10-28T01:56:06+00:00\",\"dateModified\":\"2024-11-26T06:51:43+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/atmokpo.com\/w\/29690\/\"},\"wordCount\":24,\"publisher\":{\"@id\":\"https:\/\/atmokpo.com\/w\/#organization\"},\"articleSection\":[\"\ud5c8\uae45\ud398\uc774\uc2a4 \ud65c\uc6a9\"],\"inLanguage\":\"ko-KR\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/atmokpo.com\/w\/29690\/\",\"url\":\"https:\/\/atmokpo.com\/w\/29690\/\",\"name\":\"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc815\ud655\ub3c4 - 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{"id":29690,"date":"2024-10-28T01:56:06","date_gmt":"2024-10-28T01:56:06","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=29690"},"modified":"2024-11-26T06:51:43","modified_gmt":"2024-11-26T06:51:43","slug":"%ed%97%88%ea%b9%85%ed%8e%98%ec%9d%b4%ec%8a%a4-%ed%8a%b8%eb%a0%8c%ec%8a%a4%ed%8f%ac%eb%a8%b8-%ed%99%9c%ec%9a%a9%ea%b0%95%ec%a2%8c-%ec%a0%95%ed%99%95%eb%8f%84","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/29690\/","title":{"rendered":"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc815\ud655\ub3c4"},"content":{"rendered":"

<\/p>\n

\ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \ud5c8\uae45\ud398\uc774\uc2a4\uc758 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ud0dc\uc2a4\ud06c\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud558\uace0, \ubaa8\ub378\uc758 \uc815\ud655\ub3c4\ub97c \ud3c9\uac00\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \ub2e4\ub8f0 \uac83\uc785\ub2c8\ub2e4. \ud5c8\uae45\ud398\uc774\uc2a4\ub294 \ub2e4\uc591\ud55c \uc0ac\uc804 \ud559\uc2b5(pre-trained) \ubaa8\ub378\uc744 \uc81c\uacf5\ud558\uc5ec NLP \uc791\uc5c5\uc5d0\uc11c \uc27d\uac8c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n

1. \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38\ub780?<\/h2>\n
\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \ub2e4\uc591\ud55c \ucd5c\uc2e0 NLP \ubaa8\ub378\uc744 \uc81c\uacf5\ud558\ub294 Python \ub77c\uc774\ube0c\ub7ec\ub9ac\uc785\ub2c8\ub2e4. \ube44\uc9c0\ub3c4 \ud559\uc2b5, \uc9c0\ub3c4 \ud559\uc2b5\uc744 \ud1b5\ud574 \ubaa8\ub378\uc744 \ud6c8\ub828\uc2dc\ud0ac \uc218 \uc788\uc73c\uba70, \ud2b9\ud788 BERT, GPT, T5 \ub4f1\uc758 \uc804\uc774 \ud559\uc2b5 \ubaa8\ub378\uc744 \uc27d\uac8c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n

1.1. \uc8fc\uc694 \ud2b9\uc9d5<\/h3>\n

\uc0ac\uc804 \ud559\uc2b5\ub41c \ubaa8\ub378 \ub2e4\uc6b4\ub85c\ub4dc \ubc29\ubc95\uc774 \uac04\ud3b8\ud558\ub2e4.<\/li>\n
PyTorch \ubc0f TensorFlow\uc640 \ud638\ud658\ub41c\ub2e4.<\/li>\n

\ub2e4\uc591\ud55c NLP \ud0dc\uc2a4\ud06c\ub97c \uc704\ud55c \uac04\ub2e8\ud55c API\ub97c \uc81c\uacf5\ud55c\ub2e4.<\/li>\n<\/ul>\n

2. \ud658\uacbd \uad6c\ucd95<\/h2>\n

\ucf54\ub4dc\ub97c \uc2e4\ud589\ud558\uae30 \uc704\ud574 \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc124\uce58\ud569\ub2c8\ub2e4. \uc544\ub798\uc758 \uba85\ub839\uc5b4\ub85c \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ubc0f \uad00\ub828 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc124\uce58\ud569\ub2c8\ub2e4:<\/p>\n

pip install transformers torch<\/code><\/pre>\n3. \ub370\uc774\ud130\uc14b \uc900\ube44<\/h2>\n\uc774\uc81c \uac04\ub2e8\ud55c \uac10\uc815 \ubd84\uc11d\uc744 \uc704\ud55c \ub370\uc774\ud130\ub97c \uc900\ube44\ud574\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \ub370\uc774\ud130\ub294 \uae0d\uc815\uc801 \ubc0f \ubd80\uc815\uc801 \ub9ac\ubdf0\ub85c \uad6c\uc131\ub429\ub2c8\ub2e4.<\/p>\n
import pandas as pd\n\ndata = {\n    \"text\": [\"\uc774 \uc601\ud654\ub294 \uc815\ub9d0 \uc7ac\ubbf8\uc788\uc5b4\uc694!\", \"\ucd5c\uc545\uc758 \uc601\ud654\uc600\uc2b5\ub2c8\ub2e4.\", \"\uc5b4\ub9c8\uc5b4\ub9c8\ud55c \uc2a4\ud1a0\ub9ac\ub77c\uc778!\", \"\ub2e4\uc2dc\ub294 \ubcf4\uace0 \uc2f6\uc9c0 \uc54a\uc544\uc694.\"],\n    \"label\": [1, 0, 1, 0]  # 1: \uae0d\uc815, 0: \ubd80\uc815\n}\n\ndf = pd.DataFrame(data)\nprint(df)<\/code><\/pre>\n4. \ubaa8\ub378 \ubd88\ub7ec\uc624\uae30 \ubc0f \ub370\uc774\ud130 \uc804\ucc98\ub9ac<\/h2>\n\ud5c8\uae45\ud398\uc774\uc2a4 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc0ac\uc804 \ud559\uc2b5\ub41c BERT \ubaa8\ub378\uc744 \ubd88\ub7ec\uc624\uace0, \ub370\uc774\ud130\ub97c \uc804\ucc98\ub9ac\ud569\ub2c8\ub2e4.<\/p>\n
from transformers import BertTokenizer\n\ntokenizer = BertTokenizer.from_pretrained('bert-base-uncased')\n\ndef tokenize_function(examples):\n    return tokenizer(examples['text'], padding=\"max_length\", truncation=True)\n\ntokenized_data = df.apply(tokenize_function, axis=1)\nprint(tokenized_data.head())<\/code><\/pre>\n5. \ubaa8\ub378 \ud6c8\ub828<\/h2>\n\ubaa8\ub378\uc744 \ud6c8\ub828\ud558\uae30 \uc704\ud574 PyTorch\ub97c \uc0ac\uc6a9\ud558\uc5ec \ud6c8\ub828 \ub8e8\ud504\ub97c \uc124\uc815\ud558\uace0, \ubaa8\ub378\uc744 \ud559\uc2b5\uc2dc\ud0b5\ub2c8\ub2e4.<\/p>\n
import torch\nfrom transformers import BertForSequenceClassification\nfrom torch.utils.data import DataLoader, Dataset\n\nclass ReviewDataset(Dataset):\n    def __init__(self, texts, labels):\n        self.texts = texts\n        self.labels = labels\n\n    def __len__(self):\n        return len(self.texts)\n\n    def __getitem__(self, idx):\n        return {\n            'input_ids': self.texts[idx]['input_ids'],\n            'attention_mask': self.texts[idx]['attention_mask'],\n            'labels': torch.tensor(self.labels[idx])\n        }\n\n# \ub370\uc774\ud130\uc14b \uc0dd\uc131\ndataset = ReviewDataset(tokenized_data.tolist(), df['label'].tolist())\ndataloader = DataLoader(dataset, batch_size=2, shuffle=True)\n\n# \ubaa8\ub378 \ubd88\ub7ec\uc624\uae30\nmodel = BertForSequenceClassification.from_pretrained('bert-base-uncased', num_labels=2)\n\n# \ud6c8\ub828\uc744 \uc704\ud55c \uc635\ud2f0\ub9c8\uc774\uc800 \uc124\uc815\noptimizer = torch.optim.AdamW(model.parameters(), lr=1e-5)\n\n# \ubaa8\ub378 \ud6c8\ub828\nmodel.train()\nfor epoch in range(3):  # \uc5d0\ud3ec\ud06c \uc218\n    for batch in dataloader:\n        optimizer.zero_grad()\n        outputs = model(input_ids=batch['input_ids'], attention_mask=batch['attention_mask'], labels=batch['labels'])\n        loss = outputs.loss\n        loss.backward()\n        optimizer.step()\n\nprint(\"\ubaa8\ub378 \ud6c8\ub828 \uc644\ub8cc!\")<\/code><\/pre>\n6. \uc815\ud655\ub3c4 \ud3c9\uac00<\/h2>\n\ubaa8\ub378\uc758 \uc815\ud655\ub3c4\ub97c \ud3c9\uac00\ud558\uae30 \uc704\ud574 \ud14c\uc2a4\ud2b8 \ub370\uc774\ud130\uc14b\uc744 \uc900\ube44\ud558\uace0, \uc608\uce21\uc744 \uc218\ud589\ud569\ub2c8\ub2e4.<\/p>\n
from sklearn.metrics import accuracy_score\n\n# \ud14c\uc2a4\ud2b8 \ub370\uc774\ud130\uc14b (\uc784\uc758\ub85c \uc0dd\uc131\ub41c \uc608\uc2dc)\ntest_data = {\n    \"text\": [\"\uc774 \uc601\ud654\ub294 \uae30\ub300 \uc774\uc0c1\uc774\uc5c8\uc5b4\uc694!\", \"\ub108\ubb34 \uc9c0\ub8e8\ud588\uace0, \uc2ac\ud508 \uc774\uc57c\uae30\uc600\uc5b4\uc694.\"],\n    \"label\": [1, 0]\n}\ntest_df = pd.DataFrame(test_data)\ntest_tokenized = test_df.apply(tokenize_function, axis=1)\n\n# \uc608\uce21 \uc218\ud589\nmodel.eval()\npredictions = []\nwith torch.no_grad():\n    for test_input in test_tokenized:\n        outputs = model(input_ids=test_input['input_ids'], attention_mask=test_input['attention_mask'])\n        predictions.append(torch.argmax(outputs.logits, dim=-1).item())\n\n# \uc815\ud655\ub3c4 \uacc4\uc0b0\naccuracy = accuracy_score(test_df['label'], predictions)\nprint(f\"\ubaa8\ub378 \uc815\ud655\ub3c4: {accuracy * 100:.2f}%\")<\/code><\/pre>\n7. \uacb0\ub860<\/h2>\n\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uba74 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ud0dc\uc2a4\ud06c\ub97c \uc27d\uace0 \ube60\ub974\uac8c \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uc744 \ud1b5\ud574 \uc791\uc740 \ub370\uc774\ud130\uc14b\uc5d0\uc11c\ub3c4 \uc88b\uc740 \uc131\ub2a5\uc744 \uc5bb\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc815\ud655\ub3c4\ub97c \ud3c9\uac00\ud558\ub294 \uacfc\uc815\uacfc \uc774\ub97c \ud1b5\ud574 \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \uc774\ud574\ud558\ub294 \uac83\uc740 \ub525\ub7ec\ub2dd\uc744 \ubc30\uc6b0\ub294 \ub370 \uc911\uc694\ud55c \ubd80\ubd84\uc785\ub2c8\ub2e4.<\/p>\n
8. \ucc38\uace0 \uc790\ub8cc<\/h2>\n\nHugging Face Transformers Documentation<\/a><\/li>\n
PyTorch Official Website<\/a><\/li>\n
Scikit-Learn Documentation<\/a><\/li>\n<\/ul>\n<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"\ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \ud5c8\uae45\ud398\uc774\uc2a4\uc758 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ud0dc\uc2a4\ud06c\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud558\uace0, \ubaa8\ub378\uc758 \uc815\ud655\ub3c4\ub97c \ud3c9\uac00\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \ub2e4\ub8f0 \uac83\uc785\ub2c8\ub2e4. \ud5c8\uae45\ud398\uc774\uc2a4\ub294 \ub2e4\uc591\ud55c \uc0ac\uc804 \ud559\uc2b5(pre-trained) \ubaa8\ub378\uc744 \uc81c\uacf5\ud558\uc5ec NLP \uc791\uc5c5\uc5d0\uc11c \uc27d\uac8c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. 1. \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38\ub780? \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \ub2e4\uc591\ud55c \ucd5c\uc2e0 NLP \ubaa8\ub378\uc744 \uc81c\uacf5\ud558\ub294 Python \ub77c\uc774\ube0c\ub7ec\ub9ac\uc785\ub2c8\ub2e4. \ube44\uc9c0\ub3c4 \ud559\uc2b5, \uc9c0\ub3c4 \ud559\uc2b5\uc744 \ud1b5\ud574 \ubaa8\ub378\uc744 \ud6c8\ub828\uc2dc\ud0ac \uc218 \uc788\uc73c\uba70, \ud2b9\ud788 BERT, … \ub354 \ubcf4\uae30 “\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc815\ud655\ub3c4”<\/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":[30],"tags":[],"class_list":["post-29690","post","type-post","status-publish","format-standard","hentry","category-30"],"yoast_head":"\n\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc815\ud655\ub3c4 - \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\/29690\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc815\ud655\ub3c4 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"\ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \ud5c8\uae45\ud398\uc774\uc2a4\uc758 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP) \ud0dc\uc2a4\ud06c\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud558\uace0, \ubaa8\ub378\uc758 \uc815\ud655\ub3c4\ub97c \ud3c9\uac00\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \ub2e4\ub8f0 \uac83\uc785\ub2c8\ub2e4. \ud5c8\uae45\ud398\uc774\uc2a4\ub294 \ub2e4\uc591\ud55c \uc0ac\uc804 \ud559\uc2b5(pre-trained) \ubaa8\ub378\uc744 \uc81c\uacf5\ud558\uc5ec NLP \uc791\uc5c5\uc5d0\uc11c \uc27d\uac8c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. 1. \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38\ub780? \ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub79c\uc2a4\ud3ec\uba38 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \ub2e4\uc591\ud55c \ucd5c\uc2e0 NLP \ubaa8\ub378\uc744 \uc81c\uacf5\ud558\ub294 Python \ub77c\uc774\ube0c\ub7ec\ub9ac\uc785\ub2c8\ub2e4. \ube44\uc9c0\ub3c4 \ud559\uc2b5, \uc9c0\ub3c4 \ud559\uc2b5\uc744 \ud1b5\ud574 \ubaa8\ub378\uc744 \ud6c8\ub828\uc2dc\ud0ac \uc218 \uc788\uc73c\uba70, \ud2b9\ud788 BERT, … \ub354 \ubcf4\uae30 "\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc815\ud655\ub3c4"\" \/>\n<meta property=\"og:url\" content=\"https:\/\/atmokpo.com\/w\/29690\/\" \/>\n<meta property=\"og:site_name\" content=\"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"article:published_time\" content=\"2024-10-28T01:56:06+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-11-26T06:51:43+00:00\" \/>\n<meta name=\"author\" content=\"root\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@bebubo4\" \/>\n<meta name=\"twitter:site\" content=\"@bebubo4\" \/>\n<meta name=\"twitter:label1\" content=\"\uae00\uc4f4\uc774\" \/>\n\t<meta name=\"twitter:data1\" content=\"root\" \/>\n\t<meta name=\"twitter:label2\" content=\"\uc608\uc0c1 \ub418\ub294 \ud310\ub3c5 \uc2dc\uac04\" \/>\n\t<meta name=\"twitter:data2\" content=\"1\ubd84\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/atmokpo.com\/w\/29690\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/atmokpo.com\/w\/29690\/\"},\"author\":{\"name\":\"root\",\"@id\":\"https:\/\/atmokpo.com\/w\/#\/schema\/person\/91b6b3b138fbba0efb4ae64b1abd81d7\"},\"headline\":\"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc815\ud655\ub3c4\",\"datePublished\":\"2024-10-28T01:56:06+00:00\",\"dateModified\":\"2024-11-26T06:51:43+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/atmokpo.com\/w\/29690\/\"},\"wordCount\":24,\"publisher\":{\"@id\":\"https:\/\/atmokpo.com\/w\/#organization\"},\"articleSection\":[\"\ud5c8\uae45\ud398\uc774\uc2a4 \ud65c\uc6a9\"],\"inLanguage\":\"ko-KR\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/atmokpo.com\/w\/29690\/\",\"url\":\"https:\/\/atmokpo.com\/w\/29690\/\",\"name\":\"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, \uc815\ud655\ub3c4 - 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