{"id":79894,"url":"https://github.com/taki0112/awesome-deeplearning-study","name":"awesome-deeplearning-study","description":"Summary of DeepLearning (Korean and English are included)","projects_count":92,"last_synced_at":"2026-08-19T05:00:32.100Z","repository":{"id":43946186,"uuid":"104418550","full_name":"taki0112/Awesome-DeepLearning-Study","owner":"taki0112","description":"Summary of DeepLearning (Korean and English are included)","archived":false,"fork":false,"pushed_at":"2018-12-27T08:39:29.000Z","size":94473,"stargazers_count":99,"open_issues_count":0,"forks_count":23,"subscribers_count":9,"default_branch":"master","last_synced_at":"2026-07-30T18:04:59.225Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/taki0112.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-09-22T01:52:11.000Z","updated_at":"2026-05-14T03:40:56.000Z","dependencies_parsed_at":"2022-09-09T20:01:03.345Z","dependency_job_id":null,"html_url":"https://github.com/taki0112/Awesome-DeepLearning-Study","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/taki0112/Awesome-DeepLearning-Study","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/taki0112%2FAwesome-DeepLearning-Study","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/taki0112%2FAwesome-DeepLearning-Study/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/taki0112%2FAwesome-DeepLearning-Study/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/taki0112%2FAwesome-DeepLearning-Study/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/taki0112","download_url":"https://codeload.github.com/taki0112/Awesome-DeepLearning-Study/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/taki0112%2FAwesome-DeepLearning-Study/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":36776293,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-08-06T04:43:03.162Z","status":"online","status_checked_at":"2026-08-19T02:00:06.185Z","response_time":54,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"created_at":"2024-11-23T23:57:38.406Z","updated_at":"2026-08-19T05:00:32.100Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["GAN, VAE","TechBlog","DeepLearning Lecture","Tensorflow Tutorial","Mathematics","etc","NLP","Pytorch Tutorial","Pre-processing","DeepLearning Tutorial","PR12 (Korean)","CheatSheet","Theory","MachineLearning Lecture"],"sub_categories":["Korean","English"],"readme":"# DeepLearning-Summary\n*Continually updating...*\n\n## PR12 (Korean)\n* [PR12-Season1](https://www.youtube.com/playlist?list=PLWKf9beHi3Tg50UoyTe6rIm20sVQOH1br)\n* [PR12-Season2](https://www.youtube.com/playlist?list=PLWKf9beHi3TgstcIn8K6dI_85_ppAxzB8)\n* [Sung-Kim-PR12](https://www.youtube.com/watch?v=auKdde7Anr8\u0026list=PLlMkM4tgfjnJhhd4wn5aj8fVTYJwIpWkS)\n* [PR12-archive](https://jamiekang.github.io/archives/)\n\n## Pre-processing\n* [python-library](http://www.lfd.uci.edu/~gohlke/pythonlibs/)\n* [Image-augmentation](https://github.com/aleju/imgaug)\n\n## CheatSheet\n* [shervine](https://stanford.edu/~shervine/) **(recommend)**\n\n## Mathematics\n#### English\n* [Probability-and-Statistics-Cookbook](http://statistics.zone/)\n* [bayes-nn](https://github.com/sjchoi86/bayes-nn)\n* [Mathematics-for-Machine-Learning](https://mml-book.github.io/)\n* [Mathematics-for-Machine-Learning_2](https://www.doc.ic.ac.uk/~mpd37/teaching/2017/496/notes.pdf?fbclid=IwAR0qShb6-PpjAd9RvLuAmmL2dWTeg1OY4oDGutSxOJcWXXiL3MHdnP3PsCs)\n\n#### Korean\n* [수포자를 위한 머신러닝](https://github.com/taki0112/Awesome-DeepLearning-Study/blob/master/file/%EC%88%98%ED%8F%AC%EC%9E%90%EB%A5%BC%20%EC%9C%84%ED%95%9C%20%EB%A8%B8%EC%8B%A0%EB%9F%AC%EB%8B%9D.pdf)\n* [Mathematics-Cookbook](https://github.com/taki0112/Awesome-DeepLearning-Study/blob/master/file/Mathematics-Cookbook.pdf)\n* [Dimension-Reduction](https://github.com/taki0112/DeepLearning-Summary/raw/master/file/Dimensionality_Reduction.pdf)\n* [Pattern-Recognition](http://norman3.github.io/prml/)\n* [공돌이의 수학정리 노트](https://wikidocs.net/book/563)\n* [Convex-Optimization](https://wikidocs.net/18720)\n\n## Theory\n#### English\n* [Machine-Learning-glossary](https://developers.google.com/machine-learning/glossary/)\n* [Backpropagation-In-Convolutional-Neural-Networks](http://www.jefkine.com/general/2016/09/05/backpropagation-in-convolutional-neural-networks/)\n* [1x1-Convolution](http://iamaaditya.github.io/2016/03/one-by-one-convolution/)\n* [SNU-TF](https://drive.google.com/drive/folders/0B8z5oUpB2DysbFNEOWxfVDh5VW8)\n* [Object-Detection](http://www.telesens.co/2018/03/11/object-detection-and-classification-using-r-cnns/)\n\n#### Korean\n* [K-MOOC_lecture](http://www.kmooc.kr/)\n* [python_lecture](https://www.youtube.com/playlist?list=PLBHVuYlKEkUJvRVv9_je9j3BpHwGHSZHz\u0026disable_polymer=true)\n* [딥러닝 이론에서 실습까지](https://drive.google.com/file/d/0B-qyuGELhRZ6dGhFeUNVaFNPbms/view)\n* [Machine-Learning](http://sanghyukchun.github.io/)\n* [Korea-Univ-Jaegul-Choo](https://www.youtube.com/channel/UCsEQc1-iFbu_yHvMd1vqwFQ/playlists)\n\n## TechBlog\n#### English\n* [GAN-wiseodd](https://wiseodd.github.io/techblog/)\n* [Peter's notes](http://peterroelants.github.io/)\n* [Colah](http://colah.github.io/)\n* [Distill](https://distill.pub/)\n* [pyimagesearch](https://www.pyimagesearch.com/author/adrian/) **(recommend)**\n* [Neurohive](https://neurohive.io/en/#pll_switcher) **(recommend)**\n* [Papers with code](https://paperswithcode.com/?ref=semscholar) **(recommend)**\n\n#### Korean\n* [Carpedm20](http://carpedm20.github.io/)\n* [Lunit](https://blog.lunit.io/)\n* [LAON-PEOPLE](http://blog.naver.com/laonple/220469250655)\n* [Deepest](http://deepestdocs.readthedocs.io/en/latest/)\n* [Sung-Kim_Summary](http://pythonkim.tistory.com/notice/25)\n* [조대협](http://bcho.tistory.com/category/%EB%B9%85%EB%8D%B0%EC%9D%B4%ED%83%80/%EB%A8%B8%EC%8B%A0%EB%9F%AC%EB%8B%9D)\n* [Chris-송호연](https://brunch.co.kr/@chris-song#articles)\n* [ratsgo-blog](https://ratsgo.github.io/blog/categories/)\n* [Keunwoo-choi](http://keunwoochoi.blogspot.kr/)\n\n## DeepLearning Lecture\n#### English\n* [Coursera, Machine Learning - Andrew Ng](https://www.coursera.org/)\n* [DLSS, RLSS](http://videolectures.net/deeplearning2017_montreal/)\n* [fast.ai](http://course.fast.ai/?utm_campaign=Revue+newsletter\u0026utm_medium=Newsletter\u0026utm_source=revue)\n* [Siraj Raval](https://www.youtube.com/channel/UCWN3xxRkmTPmbKwht9FuE5A)\n* [cs231n](https://www.youtube.com/watch?v=vT1JzLTH4G4\u0026list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv)\n#### Korean\n* [Sung-Kim](https://www.youtube.com/channel/UCML9R2ol-l0Ab9OXoNnr7Lw)\n* [최신논문으로 시작하는 딥러닝](http://www.edwith.org/deeplearningchoi/)\n* [cs231n](https://www.youtube.com/playlist?list=PL1Kb3QTCLIVtyOuMgyVgT-OeW0PYXl3j5)\n* [Terry-deeplearning-talk](https://www.youtube.com/watch?v=D4zqigCb8co\u0026list=PL0oFI08O71gKEXITQ7OG2SCCXkrtid7Fq)\n* [Reienforcement-slide](https://www.slideshare.net/WoongwonLee/ss-78783597?from_m_app=android)\n* [NaverD2](https://www.youtube.com/watch?v=soZXAH3leeQ\u0026list=PLsFtzQAC8dDetav3jSCKB_MXwvUn7yfJS)\n* [Enjoy-DL](https://www.facebook.com/notes/enjoydl/deep-leaning-video-links/1227281394020895/)\n\n## MachineLearning Lecture\n#### English\n* [Awesome-Machine-Learning-Projects](https://ml-showcase.com/)\n#### Korean\n* [KAIST_lecture](https://www.youtube.com/watch?v=4w1lidx6mV4\u0026list=PLbhbGI_ppZIRPeAjprW9u9A46IJlGFdLn)\n* [Summary_slide](https://www.slideshare.net/SGoodKim/machine-learning-bysogood-80076209)\n\n## DeepLearning Tutorial\n#### English\n* [sjchoi_tutorial](https://github.com/sjchoi86/dl_tutorials_10weeks)\n* [DeepLearningZeroToAll](https://github.com/hunkim/DeepLearningZeroToAll)\n#### Korean\n* [Yongho Ha_slide](https://www.slideshare.net/yongho/ss-79607172)\n* [Namhyuk-Ahn](https://github.com/nmhkahn/deep_learning_tutorial)\n* [Chanwoo-Lee](http://nbviewer.jupyter.org/format/slides/gist/leechanwoo/)\n\n## Tensorflow Tutorial\n#### Korean\n* [TensorFlowKR-2017-talk-bestpractice_slide](https://github.com/wookayin)\n* [Golbin_tutorial](https://github.com/golbin/TensorFlow-Tutorials)\n\n### English\n* [Keras + Tensorflow for image](https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html)\n* [Stanford_Tensorflow_tutorial](http://web.stanford.edu/class/cs20si/)\n\n## Pytorch Tutorial\n### English\n* [yunjey](https://github.com/yunjey/pytorch-tutorial)\n* [PyTorchZeroToAll](https://github.com/hunkim/PyTorchZeroToAll)\n### Korean\n* [Choi-Gunho](https://github.com/GunhoChoi/PyTorch-FastCampus)\n\n## GAN, VAE\n#### English\n* [illinois_slide](http://slazebni.cs.illinois.edu/spring17/lec11_gan.pdf)\n* [Delving-deep-into-GANs](https://github.com/GKalliatakis/Delving-deep-into-GANs)\n* [Wasserstein GAN in Keras](https://myurasov.github.io/2017/09/24/wasserstein-gan-keras.html?r)\n* [tf-gan-comparison](https://github.com/khanrc/tf.gans-comparison)\n* [tf-gan-colletion](https://github.com/hwalsuklee/tensorflow-generative-model-collections)\n* [how-to-train-gan](https://github.com/taki0112/Awesome-DeepLearning-Study/raw/master/file/How_To_Train_a_GAN.pdf)\n#### Korean\n* [Hwalsuk Lee_slide](https://mega.nz/#!tBo3zAKR!yE6tZ0g-GyUyizDf7uglDk2_ahP-zj5trVZSLW3GAjw)\n* [Jaejun Yoo_blog](http://jaejunyoo.blogspot.com/search/label/GAN)\n* [Style-Transfer](https://github.com/taki0112/DeepLearning-Summary/raw/master/file/Style%20Transfer.pdf)\n\n## NLP\n#### English\n* [stanford-NLP](https://www.youtube.com/watch?v=OQQ-W_63UgQ\u0026list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6)\n* [oxford-NLP](https://github.com/oxford-cs-deepnlp-2017/lectures), [video](https://www.youtube.com/watch?v=RP3tZFcC2e8\u0026list=PL613dYIGMXoZBtZhbyiBqb0QtgK6oJbpm)\n* [NLP-DL-Lecture-Note](https://github.com/nyu-dl/NLP_DL_Lecture_Note)\n* [NeuralDialogPaper](https://github.com/snakeztc/NeuralDialogPapers)\n* [Word2Vec](http://adventuresinmachinelearning.com/word2vec-tutorial-tensorflow/)\n#### Korean\n* [Word2Vec](https://dreamgonfly.github.io/machine/learning,/natural/language/processing/2017/08/16/word2vec_explained.html)\n* [RNN](http://jaejunyoo.blogspot.com/2017/06/anyone-can-learn-to-code-LSTM-RNN-Python.html)\n* [NaverD2_lecture](https://www.youtube.com/watch?v=r0veZ_WV0sA\u0026list=PLsFtzQAC8dDdIqSY3o5XF_IBIgSLcyzTd)\n\n\n## etc\n#### English\n* [visualize-neural-net](https://github.com/Cloud-CV/Fabrik)\n* [visualize-convoulution](https://github.com/vdumoulin/conv_arithmetic)\n* [visualize-GAN](https://reiinakano.github.io/gan-playground/)\n* [visualize-learning_rate](http://www.benfrederickson.com/numerical-optimization/)\n#### Korean\n* [Medical-AI_slide](https://www.slideshare.net/hyunseokmin/applying-deep-learning-to-medical-data?from_m_app=android)\n\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/taki0112%2Fawesome-deeplearning-study/projects"}