{"id":27825626,"url":"https://github.com/davidADSP/Generative_Deep_Learning_2nd_Edition","last_synced_at":"2025-05-01T19:05:54.217Z","repository":{"id":113037522,"uuid":"474150870","full_name":"davidADSP/Generative_Deep_Learning_2nd_Edition","owner":"davidADSP","description":"The official code repository for the second edition of the O'Reilly book Generative Deep Learning: Teaching Machines to Paint, Write, Compose and Play.","archived":false,"fork":false,"pushed_at":"2024-06-02T14:32:23.000Z","size":14477,"stargazers_count":1245,"open_issues_count":32,"forks_count":485,"subscribers_count":27,"default_branch":"main","last_synced_at":"2025-04-08T01:37:34.543Z","etag":null,"topics":["chatgpt","dalle2","data-science","deep-learning","diffusion-models","generative-adversarial-network","gpt-3","machine-learning","python","stable-diffusion","tensorflow"],"latest_commit_sha":null,"homepage":"https://www.oreilly.com/library/view/generative-deep-learning/9781098134174/","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/davidADSP.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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,"publiccode":null,"codemeta":null}},"created_at":"2022-03-25T20:11:14.000Z","updated_at":"2025-04-07T01:05:50.000Z","dependencies_parsed_at":"2024-08-02T01:38:30.323Z","dependency_job_id":null,"html_url":"https://github.com/davidADSP/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/davidADSP%2FGenerative_Deep_Learning_2nd_Edition","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/davidADSP%2FGenerative_Deep_Learning_2nd_Edition/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/davidADSP%2FGenerative_Deep_Learning_2nd_Edition/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/davidADSP%2FGenerative_Deep_Learning_2nd_Edition/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/davidADSP","download_url":"https://codeload.github.com/davidADSP/Generative_Deep_Learning_2nd_Edition/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251930207,"owners_count":21666773,"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":["chatgpt","dalle2","data-science","deep-learning","diffusion-models","generative-adversarial-network","gpt-3","machine-learning","python","stable-diffusion","tensorflow"],"created_at":"2025-05-01T19:01:32.136Z","updated_at":"2025-05-01T19:05:54.210Z","avatar_url":"https://github.com/davidADSP.png","language":"Jupyter Notebook","readme":"# 🦜 Generative Deep Learning - 2nd Edition Codebase\n\nThe official code repository for the second edition of the O'Reilly book *Generative Deep Learning: Teaching Machines to Paint, Write, Compose and Play*.\n\n[O'Reilly link](https://www.oreilly.com/library/view/generative-deep-learning/9781098134174/)\n\n[Amazon US link](https://www.amazon.com/Generative-Deep-Learning-Teaching-Machines/dp/1098134184/)\n\n\u003cimg src=\"img/book_cover.png\" width=\"300px\"\u003e\n\n## 📖 Book Chapters\n\nBelow is a outline of the book chapters:\n\n*Part I: Introduction to Generative Deep Learning*\n\n1. Generative Modeling\n2. Deep Learning\n\n*Part II: Methods*\n\n3. Variational Autoencoders\n4. Generative Adversarial Networks\n5. Autoregressive Models\n6. Normalizing Flows\n7. Energy-Based Models\n8. Diffusion Models\n\n*Part III: Applications*\n\n9. Transformers\n10. Advanced GANs\n11. Music Generation\n12. World Models\n13. Multimodal Models\n14. Conclusion\n\n## 🌟 Star History\n\n\u003cimg src=\"https://api.star-history.com/svg?repos=davidADSP/Generative_Deep_Learning_2nd_Edition\u0026type=Date\" width=\"500px\"\u003e\n\n## 🚀 Getting Started\n\n### Kaggle API\n\nTo download some of the datasets for the book, you will need a Kaggle account and an API token. To use the Kaggle API:\n\n1. Sign up for a [Kaggle account](https://www.kaggle.com).\n2. Go to the 'Account' tab of your user profile\n3. Select 'Create API Token'. This will trigger the download of `kaggle.json`, a file containing your API credentials.\n\n### The .env file\n\nCreate a file called `.env` in the root directory, containing the following values (replacing the Kaggle username and API key with the values from the JSON):\n\n```\nJUPYTER_PORT=8888\nTENSORBOARD_PORT=6006\nKAGGLE_USERNAME=\u003cyour_kaggle_username\u003e\nKAGGLE_KEY=\u003cyour_kaggle_key\u003e\n```\n\n### Get set up with Docker\n\nThis codebase is designed to be run with [Docker](https://docs.docker.com/get-docker/).\n\nIf you've never used Docker before, don't worry! I have included a guide to Docker in the [Docker README](./docs/docker.md) file in this repository. This includes a full run through of why Docker is awesome and a brief guide to the `Dockerfile` and `docker-compose.yml` for this project.\n\n### Building the Docker image\n\nIf you do not have a GPU, run the following command:\n\n```\ndocker compose build\n```\n\nIf you do have a GPU that you wish to use, run the following command:\n\n```\ndocker compose -f docker-compose.gpu.yml build\n```\n\n### Running the container\n\nIf you do not have a GPU, run the following command:\n\n```\ndocker compose up\n```\n\nIf you do have a GPU that you wish to use, run the following command:\n\n```\ndocker compose -f docker-compose.gpu.yml up\n```\n\nJupyter will be available in your local browser, on the port specified in your env file - for example\n\n```\nhttp://localhost:8888\n```\n\nThe notebooks that accompany the book are available in the `/notebooks` folder, organized by chapter and example.\n\n## 🏞️ Downloading data\n\nThe codebase comes with an in-built data downloader helper script.\n\nRun the data downloader as follows (from outside the container), choosing one of the named datasets below:\n\n```\nbash scripts/download.sh [faces, bricks, recipes, flowers, wines, cellosuites, chorales]\n```\n\n## 📈 Tensorboard\n\nTensorboard is really useful for monitoring experiments and seeing how your model training is progressing.\n\nTo launch Tensorboard, run the following script (from outside the container):\n* `\u003cCHAPTER\u003e` - the required chapter (e.g. `03_vae`)\n* `\u003cEXAMPLE\u003e` - the required example (e.g. `02_vae_fashion`)\n\n```\nbash scripts/tensorboard.sh \u003cCHAPTER\u003e \u003cEXAMPLE\u003e\n```\n\nTensorboard will be available in your local browser on the port specified in your `.env` file - for example:\n```\nhttp://localhost:6006\n```\n\n## ☁️ Using a cloud virtual machine\n\nTo set up a virtual machine with GPU in Google Cloud Platform, follow the instructions in the [Google Cloud README](./docs/googlecloud.md) file in this repository.\n\n## 📦 Other resources\n\nSome of the examples in this book are adapted from the excellent open source implementations that are available through the [Keras website](https://keras.io/examples/generative/). I highly recommend you check out this resource as new models and examples are constantly being added.\n\n\n","funding_links":[],"categories":["Documentation and examples"],"sub_categories":["Documentation, lists, guides, or examples"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FdavidADSP%2FGenerative_Deep_Learning_2nd_Edition","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FdavidADSP%2FGenerative_Deep_Learning_2nd_Edition","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FdavidADSP%2FGenerative_Deep_Learning_2nd_Edition/lists"}