{"id":16360053,"url":"https://github.com/frgfm/dl-playground","last_synced_at":"2025-08-01T07:31:19.497Z","repository":{"id":110055948,"uuid":"161053090","full_name":"frgfm/dl-playground","owner":"frgfm","description":"Exercises \u0026 challenges for aspiring deep learners","archived":false,"fork":false,"pushed_at":"2019-01-27T20:16:35.000Z","size":30,"stargazers_count":10,"open_issues_count":0,"forks_count":7,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-07T14:51:23.419Z","etag":null,"topics":["backpropagation","calculus","deep-learning","linear-algebra","pytorch","udacity","udacity-deep-learning"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/frgfm.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,"publiccode":null,"codemeta":null}},"created_at":"2018-12-09T15:26:12.000Z","updated_at":"2021-12-02T14:22:11.000Z","dependencies_parsed_at":"2023-04-22T18:04:45.794Z","dependency_job_id":null,"html_url":"https://github.com/frgfm/dl-playground","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/frgfm/dl-playground","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/frgfm%2Fdl-playground","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/frgfm%2Fdl-playground/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/frgfm%2Fdl-playground/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/frgfm%2Fdl-playground/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/frgfm","download_url":"https://codeload.github.com/frgfm/dl-playground/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/frgfm%2Fdl-playground/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":268185559,"owners_count":24209392,"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","status":"online","status_checked_at":"2025-08-01T02:00:08.611Z","response_time":67,"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"}},"keywords":["backpropagation","calculus","deep-learning","linear-algebra","pytorch","udacity","udacity-deep-learning"],"created_at":"2024-10-11T02:10:23.801Z","updated_at":"2025-08-01T07:31:19.258Z","avatar_url":"https://github.com/frgfm.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Deep Learning playground\nThis repository compiles different challenges for deep learning enthusiasts. It was initially dedicated to Udacity scholars from the Deep Learning nanodegree.\n\nDiving further into the different topics of the course and notebook exercises from the nanodegree [repo](https://github.com/frgfm/deep-learning-v2-pytorch), you can find the following exercises for each lesson.\n\n### Neural Network building blocks\nCreate the building blocks for your own MLP in numpy by completing two challenges:\n- Feed-forward MLP ([notebook](https://github.com/frgfm/udacity-dl-exercises/blob/master/nn-basics/mlp_basics.ipynb))\n- Full MLP back-propagation ([notebook](https://github.com/frgfm/udacity-dl-exercises/blob/master/nn-basics/full_mlp.ipynb))\n\n### Convolutional neural networks\n\nImplementing convolutional layers as part of your layer portfolio with numpy by completing two challenges:\n\n- Convolutional layers (being finalized)\n- Layer activation visualization (coming soon)\n\n### Next upcoming challenges\n- Optimizers\n- Regularization\n- Style Transfer\n- Recurrent Neural Networks\n- Generative Adversarial Networks\n- Deep Reinforcement Learning\n\n## Requirements\nThe numpy and matplotlib packages are required to properly use the repo.\nTested on the following version:\n\n```python\nimport sys\nimport numpy, matplotlib\nprint('Python %s' % '.'.join(map(str, sys.version_info[:3])))\nprint(f'Numpy {numpy.__version__}, Matplotlib {matplotlib.__version__}')\n```\n```console\nPython 3.6.5\nNumpy 1.15.4, Matplotlib 2.2.3\n```\n\n\n## How to use it\nEach lesson has a folder with a folders and other modules. The notebook will contain all the instructions.\nFork this repo to complete the exercises, and please notify the author of potential bugs/issues\n\n### Completing an exercise\nRun your jupyter notebook server in the same environment you installed the previously mentioned requirements.\nIf you are using Anaconda distribution, open your terminal (Linux/MacOS) or Anaconda prompt (Windows) and run:\n```bash\njupyter notebook\n```\nNow navigate to the corresponding folder and follow the instructions of the notebook.\n\n\n### Submitting a request / Reporting an issue\nIf you wish to submit a request or report an issue, go to the [Issues section](https://github.com/frgfm/udacity-dl-exercises/issues), and create a \"New issue\".\n\nRegarding issues, use the following format for the title:\n```\n[Lesson #] Your Issue name\n```\nExample: [Lesson 2] Adding more instructions for the layer exercise\nand these guidelines for the comment:\n- Ensure you already have restart your kernel before reporting an issue\n- Specify your setup (OS, OS version, Python version, requirements' versions)\n- Format and specify the part of the code that is an issue\n- Format and specify the error/issue that you encounter\n- If relevant, explain what you have already tried to resolve the issue\n\n\nRegarding requests, use the following title format:\n```\n[Request] Your request name\n```\nExample: [Request] Creating an exercise illustrating dropout\n\n\n## TODO\n- [x] NN Basics\n- [ ] CNN\n- [ ] Optimizers\n- [ ] Regularization\n- [ ] Reinforcement Learning\n- [ ] GANs\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffrgfm%2Fdl-playground","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffrgfm%2Fdl-playground","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffrgfm%2Fdl-playground/lists"}