\n \ucd5c\uadfc \uae08\uc735 \ubd84\uc57c\uc5d0\uc11c \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd \uae30\uc220\uc774 \ubd90\uc744 \uc774\ub8e8\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub4e4 \uae30\uc220\uc740 \ub370\uc774\ud130\ub97c \ubd84\uc11d\ud558\uace0 \uc608\uce21\ud558\uc5ec \ub354 \ub098\uc740 \ud22c\uc790 \uacb0\uc815\uc744 \ub0b4\ub9ac\uae30 \uc704\ud574 \uc0ac\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, \ud000\ud2b8 \ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc5d0\uc11c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc740 \uc911\uc694\ud55c \uc5ed\ud560\uc744 \ub9e1\uace0 \uc788\uc73c\uba70, \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\uc758 \uac10\uc131\uc744 \ubd84\uc11d\ud558\ub294 \uae30\uc220 \ub610\ud55c \ud22c\uc790 \uc804\ub7b5 \uc218\ub9bd\uc5d0 \uc720\uc6a9\ud558\uac8c \ud65c\uc6a9\ub429\ub2c8\ub2e4.\n <\/p>\n
\n \uba38\uc2e0\ub7ec\ub2dd(Machine Learning)\uc740 \ucef4\ud4e8\ud130\uac00 \uba85\uc2dc\uc801\uc73c\ub85c \ud504\ub85c\uadf8\ub798\ubc0d\ub418\uc9c0 \uc54a\uace0\ub3c4 \ub370\uc774\ud130\ub85c\ubd80\ud130 \ud559\uc2b5\ud558\uace0 \uc608\uce21\uc744 \uc218\ud589\ud560 \uc218 \uc788\ub294 \ub2a5\ub825\uc744 \ub9d0\ud569\ub2c8\ub2e4. \uba38\uc2e0\ub7ec\ub2dd\uc758 \uc8fc\uc694 \ubd84\uc57c\ub85c\ub294 \uc9c0\ub3c4 \ud559\uc2b5, \ube44\uc9c0\ub3c4 \ud559\uc2b5, \uac15\ud654 \ud559\uc2b5 \ub4f1\uc774 \uc788\uc2b5\ub2c8\ub2e4. \uc9c0\ub3c4 \ud559\uc2b5\uc5d0\uc11c\ub294 \ub808\uc774\ube14\uc774 \uc788\ub294 \ub370\uc774\ud130\ub97c \uc774\uc6a9\ud558\uc5ec \ubaa8\ub378\uc744 \ud559\uc2b5\uc2dc\ud0a4\uace0, \ube44\uc9c0\ub3c4 \ud559\uc2b5\uc5d0\uc11c\ub294 \ub808\uc774\ube14\uc774 \uc5c6\ub294 \ub370\uc774\ud130\ub97c \ud1b5\ud574 \ud328\ud134\uc744 \ucc3e\uc2b5\ub2c8\ub2e4.\n <\/p>\n
\n \ub525\ub7ec\ub2dd(Deep Learning)\uc740 \uba38\uc2e0\ub7ec\ub2dd\uc758 \ud55c \ubd84\uc57c\ub85c, \uc778\uacf5 \uc2e0\uacbd\ub9dd\uc744 \uae30\ubc18\uc73c\ub85c \ud55c \ubaa8\ub378\uc744 \uc774\uc6a9\ud558\uc5ec \ub370\uc774\ud130\ub97c \ud559\uc2b5\ud558\ub294 \uae30\ubc95\uc785\ub2c8\ub2e4. \ub525\ub7ec\ub2dd\uc740 \uc790\ub3d9\uc73c\ub85c \ud2b9\uc9d5\uc744 \ucd94\ucd9c\ud558\uace0 \ubcf5\uc7a1\ud55c \ud328\ud134\uc744 \uc778\uc2dd\ud560 \uc218 \uc788\ub294 \ub2a5\ub825\uc744 \uac00\uc9c0\uace0 \uc788\uc5b4, \uc774\ubbf8\uc9c0 \uc778\uc2dd, \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ub4f1 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0\uc11c \ub110\ub9ac \uc0ac\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n
\n \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc740 \ucef4\ud4e8\ud130 \ud504\ub85c\uadf8\ub7a8\uc744 \uc774\uc6a9\ud574 \ubbf8\ub9ac \uc124\uc815\ub41c \uaddc\uce59\uc5d0 \ub530\ub77c \uc790\ub3d9\uc73c\ub85c \uac70\ub798\ub97c \uc218\ud589\ud558\ub294 \ubc29\uc2dd\uc785\ub2c8\ub2e4. \uc774\ub294 \uc2dc\uc7a5\uc758 \ubcc0\ub3d9\uc131\uc5d0 \ube60\ub974\uac8c \ubc18\uc751\ud558\uc5ec \ucd5c\uc801\uc758 \uac70\ub798 \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ub370 \ub3c4\uc6c0\uc744 \uc90d\ub2c8\ub2e4. \ub2e4\uc591\ud55c \uc54c\uace0\ub9ac\uc998\uc774 \uc0ac\uc6a9\ub420 \uc218 \uc788\uc73c\uba70, \uae30\uc220\uc801 \ubd84\uc11d, \uae30\ubcf8\uc801 \ubd84\uc11d\uc744 \uae30\ubc18\uc73c\ub85c \ud558\ub294 \ubc29\ubc95\ub860\uc774 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n
\n \uac10\uc131 \ubd84\uc11d(Sentiment Analysis)\uc740 \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\ub97c \ubd84\uc11d\ud558\uc5ec \uac10\uc815\uc744 \ubd84\ub958\ud558\ub294 \uc791\uc5c5\uc785\ub2c8\ub2e4. \uc774\ub294 \uc8fc\uc2dd \uc2dc\uc7a5\uc5d0\uc11c \ud22c\uc790\uc790\ub4e4\uc758 \uc2ec\ub9ac\ub97c \uc774\ud574\ud558\ub294 \ub370 \uc911\uc694\ud55c \uc815\ubcf4\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. \uae0d\uc815\uc801\uc778 \ub274\uc2a4 \uae30\uc0ac\uac00 \uc8fc\uc2dd \uac00\uaca9\uc5d0 \ubbf8\uce58\ub294 \uc601\ud5a5\uc740 \ubd80\uc815\uc801\uc778 \uae30\uc0ac\ubcf4\ub2e4 \ud6e8\uc52c \ud06c\uae30 \ub54c\ubb38\uc5d0, \uac10\uc131 \ubd84\uc11d\uc744 \ud1b5\ud574 \ud22c\uc790 \uacb0\uc815\uc744 \ub354\uc6b1 \ud6a8\uc728\uc801\uc73c\ub85c \ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n
\n Doc2Vec\uc740 \ub2e8\uc5b4\uc758 \uc758\ubbf8\ub97c \ubca1\ud130 \uacf5\uac04\uc5d0 \uc784\ubca0\ub529\ud558\ub294 \uae30\uc220\ub85c, \ubb38\uc11c\uc758 \uc758\ubbf8\ub97c \uc22b\uc790\ub85c \ud45c\ud604\ud560 \uc218 \uc788\uac8c \ud574\uc90d\ub2c8\ub2e4. \uc774\ub294 \uace0\ucc28\uc6d0 \uacf5\uac04\uc5d0\uc11c \ubb38\uc11c \uac04 \uc720\uc0ac\uc131\uc744 \uce21\uc815\ud558\ub294 \ub370 \uc720\uc6a9\ud569\ub2c8\ub2e4. Doc2Vec\uc740 \ub450 \uac00\uc9c0 \uc8fc\uc694 \ubaa8\ub378\uc778 Distributed Memory (DM)\uc640 Distributed Bag of Words (DBOW)\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubb38\uc11c\uc758 \ubca1\ud130\ub97c \ud559\uc2b5\ud569\ub2c8\ub2e4.\n <\/p>\n
\n \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc744 \uc704\ud574\uc11c\ub294 \ub2e4\uc591\ud55c \ub370\uc774\ud130\uac00 \ud544\uc694\ud569\ub2c8\ub2e4. \uc8fc\uc2dd\uc758 \uac00\uaca9 \ub370\uc774\ud130\uc640 \ud568\uaed8 \ub274\uc2a4 \uae30\uc0ac, \uc18c\uc15c \ubbf8\ub514\uc5b4 \ub370\uc774\ud130, \uae30\uc5c5 \uc2e4\uc801 \ubcf4\uace0\uc11c \ub4f1\ub3c4 \ud3ec\ud568\ub418\uc5b4\uc57c \ud569\ub2c8\ub2e4. \uc774 \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud558\ub294 \ubc29\ubc95\uc740 \uc6f9 \uc2a4\ud06c\ub798\ud551, API \uc0ac\uc6a9 \ub4f1\uc744 \ud1b5\ud574 \uac00\ub2a5\ud569\ub2c8\ub2e4.\n <\/p>\n
\n \uc218\uc9d1\ud55c \ub370\uc774\ud130\ub294 \ubaa8\ub378 \ud559\uc2b5\uc5d0 \uc801\ud569\ud558\ub3c4\ub85d \uc804\ucc98\ub9ac\uac00 \ud544\uc694\ud569\ub2c8\ub2e4. \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\uc758 \uacbd\uc6b0, \ubd88\uc6a9\uc5b4 \uc81c\uac70, \uc5b4\uadfc \ucd94\ucd9c, \ud1a0\ud070\ud654 \ub4f1\uc758 \uacfc\uc815\uc774 \ud544\uc694\ud569\ub2c8\ub2e4. \uc774 \uacfc\uc815\uc744 \ud1b5\ud574 \ub178\uc774\uc988\ub97c \uc904\uc774\uace0 \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud5a5\uc0c1\uc2dc\ud0ac \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n
\n Doc2Vec\uc744 \ud65c\uc6a9\ud558\uc5ec \ub274\uc2a4 \uae30\uc0ac\uc640 \uac19\uc740 \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\ub97c \ubca1\ud130\ub85c \ubcc0\ud658\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 \uac01 \ubb38\uc11c\uc758 \uc758\ubbf8\ub97c \uc218\uce58\uc801\uc73c\ub85c \ud45c\ud604\ud560 \uc218 \uc788\uc73c\uba70, \uac10\uc131 \ubd84\uc11d \ubaa8\ub378\uc744 \ud559\uc2b5\ud558\ub294 \ub370 \uc0ac\uc6a9\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n
\nfrom gensim.models import Doc2Vec, TaggedDocument\n\ndocuments = [TaggedDocument(words=['I', 'love', 'this', 'stock'], tags=['positive']),\n TaggedDocument(words=['This', 'is', 'a', 'bad', 'investment'], tags=['negative'])]\n\nmodel = Doc2Vec(vector_size=20, min_count=1, epochs=100)\nmodel.build_vocab(documents)\nmodel.train(documents, total_examples=model.corpus_count, epochs=model.epochs)\n<\/code><\/pre>\n8. \uac10\uc131 \ubd84\uc11d \ubaa8\ub378 \uac1c\ubc1c<\/h2>\n
\n \uc218\uc9d1\ud55c \ub370\uc774\ud130\ub97c Doc2Vec\uc73c\ub85c \uc784\ubca0\ub529\ud55c \ud6c4, \uac10\uc131 \ubd84\uc11d \ubaa8\ub378\uc744 \uac1c\ubc1c\ud569\ub2c8\ub2e4. \ub525\ub7ec\ub2dd \ud504\ub808\uc784\uc6cc\ud06c\ub97c \ud65c\uc6a9\ud558\uc5ec \ub2e4\uc591\ud55c \uc2e0\uacbd\ub9dd \uc544\ud0a4\ud14d\ucc98\ub97c \ud1b5\ud574 \ubaa8\ub378\uc744 \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4 RNN, LSTM, BERT \ub4f1\uc758 \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud558\uc5ec \uac10\uc131\uc744 \ubd84\ub958\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n
\nfrom keras.models import Sequential\nfrom keras.layers import Dense, LSTM, Embedding\n\nmodel = Sequential()\nmodel.add(Embedding(input_dim=vocab_size, output_dim=embedding_dim, input_length=max_length))\nmodel.add(LSTM(units=100))\nmodel.add(Dense(1, activation='sigmoid'))\nmodel.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n <\/code><\/pre>\n9. \ud2b8\ub808\uc774\ub529 \uc2e0\ud638 \uc0dd\uc131<\/h2>\n
\n \uac1c\ubc1c\ud55c \uac10\uc131 \ubd84\uc11d \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud2b8\ub808\uc774\ub529 \uc2e0\ud638\ub97c \uc0dd\uc131\ud569\ub2c8\ub2e4. \uae0d\uc815\uc801\uc778 \uac10\uc131\uc744 \uac00\uc9c4 \ub274\uc2a4 \uae30\uc0ac\uac00 \uc788\uc744 \uacbd\uc6b0 \ub9e4\uc218 \uc2e0\ud638\ub97c \ubc1c\uc0dd\uc2dc\ud0a4\uace0, \ubd80\uc815\uc801\uc778 \uae30\uc0ac\uac00 \uc788\uc744 \uacbd\uc6b0 \ub9e4\ub3c4 \uc2e0\ud638\ub97c \ubc1c\uc0dd\uc2dc\ud0ac \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub294 \uc2dc\uc7a5\uc758 \ubcc0\ub3d9\uc131\uc744 \uc608\uce21\ud558\uace0 \ucd5c\uc801\uc758 \ud22c\uc790 \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ub370 \ub3c4\uc6c0\uc744 \uc90d\ub2c8\ub2e4.\n <\/p>\n
10. \uacb0\uacfc \ubd84\uc11d \ubc0f \ud3c9\uac00<\/h2>\n
\n \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \uc131\uacfc\ub97c \ubd84\uc11d\ud558\uae30 \uc704\ud574\uc11c\ub294 \ub2e4\uc591\ud55c \uc9c0\ud45c\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud3c9\uac00\ud574\uc57c \ud569\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \uc218\uc775\ub960, \uc0e4\ud504 \ube44\uc728, \ucd5c\ub300 \ub099\ud3ed \ub4f1\uc744 \ubd84\uc11d\ud558\uc5ec \ubaa8\ub378\uc758 \uc720\ud6a8\uc131\uc744 \uac80\uc99d\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 \uc54c\uace0\ub9ac\uc998\uc758 \uac1c\uc120 \ubc29\ud5a5\uc744 \ub3c4\ucd9c\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n
11. \uacb0\ub860<\/h2>\n
\n \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uae30\uc220\uc744 \ud65c\uc6a9\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc5d0 \ub300\ud574 \uc0b4\ud3b4\ubcf4\uc558\uc2b5\ub2c8\ub2e4. Doc2Vec\uc744 \ud1b5\ud55c \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130 \uc784\ubca0\ub529\uacfc \uac10\uc131 \ubd84\uc11d\uc740 \ud000\ud2b8 \ub9e4\ub9e4\uc5d0\uc11c \uc911\uc694\ud55c \uc694\uc18c\ub85c \uc790\ub9ac \uc7a1\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc55e\uc73c\ub85c\ub3c4 \uae30\uc220\uc758 \ubc1c\uc804\uacfc \ud568\uaed8 \ub354\uc6b1 \uc815\uad50\ud558\uace0 \ud6a8\uacfc\uc801\uc778 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529 \uc804\ub7b5\uc774 \uac1c\ubc1c\ub420 \uac83\uc73c\ub85c \uae30\ub300\ub429\ub2c8\ub2e4.\n <\/p>\n
12. \ucc38\uace0 \ubb38\ud5cc<\/h2>\n\n- O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing Group.<\/li>\n
- Chatzis, S., & Potet, D. (2018). Quantitative Financial Analytics: The Path to Investment Success. Alpha Edition.<\/li>\n
- Kelleher, J. D., & Tierney, B. (2018). Data Science. The MIT Press.<\/li>\n
- Brownlee, J. (2019). Deep Learning for Time Series Forecasting. Machine Learning Mastery.<\/li>\n<\/ul>\n