{"id":23364062,"url":"https://github.com/rickiepark/generative_deep_learning_2nd_edition","last_synced_at":"2025-04-09T12:04:20.803Z","repository":{"id":164321671,"uuid":"638068295","full_name":"rickiepark/Generative_Deep_Learning_2nd_Edition","owner":"rickiepark","description":"\u003c만들면서 배우는 생성 AI 2판\u003e의 코드 저장소","archived":false,"fork":false,"pushed_at":"2025-03-26T04:09:04.000Z","size":232616,"stargazers_count":58,"open_issues_count":0,"forks_count":33,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-04-02T08:50:22.351Z","etag":null,"topics":["deep-learning","gan","generative-ai","gpt","multimodal","stable-diffusion","transformer","vae"],"latest_commit_sha":null,"homepage":"https://bit.ly/gen-dl-home","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/rickiepark.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,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2023-05-09T02:39:47.000Z","updated_at":"2025-03-27T08:28:34.000Z","dependencies_parsed_at":null,"dependency_job_id":"896895bc-f604-4253-b24b-a184d47b9c5e","html_url":"https://github.com/rickiepark/Generative_Deep_Learning_2nd_Edition","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rickiepark%2FGenerative_Deep_Learning_2nd_Edition","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rickiepark%2FGenerative_Deep_Learning_2nd_Edition/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rickiepark%2FGenerative_Deep_Learning_2nd_Edition/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rickiepark%2FGenerative_Deep_Learning_2nd_Edition/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rickiepark","download_url":"https://codeload.github.com/rickiepark/Generative_Deep_Learning_2nd_Edition/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248036064,"owners_count":21037092,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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"}},"keywords":["deep-learning","gan","generative-ai","gpt","multimodal","stable-diffusion","transformer","vae"],"created_at":"2024-12-21T13:13:55.324Z","updated_at":"2025-04-09T12:04:20.783Z","avatar_url":"https://github.com/rickiepark.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🦜 \u003c만들면서 배우는 생성 AI 2판\u003e의 코드 저장소\n\n이 저장소는 한빛미디어에서 출간한 \"만들면서 배우는 생성 AI 2판\"의 코드를 담고 있습니다. ([교보문고](https://product.kyobobook.co.kr/detail/S000208953342), [Yes24](https://www.yes24.com/Product/Goods/122338458), [알라딘](https://www.aladin.co.kr/shop/wproduct.aspx?ItemId=324278784), [한빛미디어](https://www.hanbit.co.kr/media/books/book_view.html?p_code=B6550508630))\n\n책을 구매하시면 꼭 [에러타 페이지](https://tensorflow.blog/gen-dl-2/)를 확인해 주세요. 이 저장소의 노트북은 텐서플로 2.12.0, 2.14.0에서 테스트되었습니다.\n\n1판의 깃허브는 [여기](https://github.com/rickiepark/GDL_code/)입니다.\n\n\u003cimg src=\"cover.jpeg\" width=600\u003e\n\n## 목차\nPART 1: 생성 딥러닝 소개\n* 1장: 셍성 모델링\n* 2장: 딥러닝\n  * [다층 퍼셉트론](notebooks/02_deeplearning/01_mlp/mlp.ipynb)\n  * [합성곱](notebooks/02_deeplearning/02_cnn/convolutions.ipynb)\n  * [합성곱 신경망](notebooks/02_deeplearning/02_cnn/cnn.ipynb)\n\nPART 2: 6가지 생성 모델링 방식\n* 3장: 변이형 오토인코더\n  * [오토인코더](notebooks/03_vae/01_autoencoder/autoencoder.ipynb)\n  * [변이형 오토인코더 - 패션 MNIST](notebooks/03_vae/02_vae_fashion/vae_fashion.ipynb)\n  * [변이형 오토인코더 - CelebA](notebooks/03_vae/03_vae_faces/vae_faces.ipynb)\n* 4장: 생성적 적대 신경망\n  * [DCGAN](notebooks/04_gan/01_dcgan/dcgan.ipynb)\n  * [WGAN-GP](notebooks/04_gan/02_wgan_gp/wgan_gp.ipynb)\n  * [CGAN](notebooks/04_gan/03_cgan/cgan.ipynb)\n* 5장: 자기 회귀 모델\n  * [LSTM](notebooks/05_autoregressive/01_lstm/lstm.ipynb)\n  * [PixelCNN](notebooks/05_autoregressive/02_pixelcnn/pixelcnn.ipynb)\n  * [PixelCNN - 혼합 분포](notebooks/05_autoregressive/03_pixelcnn_md/pixelcnn_md.ipynb)\n* 6장: 노멀라이징 플로 모델\n  * [RealNVP](notebooks/06_normflow/01_realnvp/realnvp.ipynb)\n* 7장: 에너지 기반 모델\n  * [EBM](notebooks/07_ebm/01_ebm/ebm.ipynb) \n* 8장: 확산 모델\n  * [확산 모델](notebooks/08_diffusion/01_ddm/ddm.ipynb) \n\nPART 3: 생성 모델링의 응용 분야\n* 9장: 트랜스포머\n  * [GPT](notebooks/09_transformer/gpt/gpt.ipynb)\n* 10장: 고급 GAN\n* 11장: 음악 생성\n  * [트랜스포머](notebooks/11_music/01_transformer/transformer.ipynb)\n  * [MuseGAN](notebooks/11_music/02_musegan/musegan.ipynb) \n* 12장: 월드 모델\n* 13장: 멀티모달 모델\n* 14장: 결론\n\n각 장의 노트북에는 구글 코랩에서 실행할 수 있는 링크가 포함되어 있습니다.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frickiepark%2Fgenerative_deep_learning_2nd_edition","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frickiepark%2Fgenerative_deep_learning_2nd_edition","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frickiepark%2Fgenerative_deep_learning_2nd_edition/lists"}