{"id":26151673,"url":"https://github.com/anker661/autograd-playground","last_synced_at":"2026-05-09T19:08:48.449Z","repository":{"id":247976120,"uuid":"825828995","full_name":"ANKer661/autograd-playground","owner":"ANKer661","description":"A simple Numpy \u0026 Python based auto differentiation system that supports visualization before and after back-propagation.","archived":false,"fork":false,"pushed_at":"2024-07-17T11:46:34.000Z","size":2977,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-08-01T12:02:47.965Z","etag":null,"topics":["auto-differentiation","autograd","computaion-graph","jupyter-notebook","numpy","python3"],"latest_commit_sha":null,"homepage":"https://mybinder.org/v2/gh/ANKer661/autograd-playground/main?labpath=autograd-playground.ipynb","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/ANKer661.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":"2024-07-08T15:22:39.000Z","updated_at":"2024-07-17T11:46:37.000Z","dependencies_parsed_at":"2024-07-17T14:14:24.926Z","dependency_job_id":"18b161af-43fa-44f0-90d8-8d1c9e76d359","html_url":"https://github.com/ANKer661/autograd-playground","commit_stats":null,"previous_names":["anker661/autograd-playground"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ANKer661/autograd-playground","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ANKer661%2Fautograd-playground","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ANKer661%2Fautograd-playground/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ANKer661%2Fautograd-playground/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ANKer661%2Fautograd-playground/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ANKer661","download_url":"https://codeload.github.com/ANKer661/autograd-playground/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ANKer661%2Fautograd-playground/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32831567,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-08T08:22:46.396Z","status":"online","status_checked_at":"2026-05-09T02:00:06.633Z","response_time":123,"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":["auto-differentiation","autograd","computaion-graph","jupyter-notebook","numpy","python3"],"created_at":"2025-03-11T06:38:19.734Z","updated_at":"2026-05-09T19:08:48.425Z","avatar_url":"https://github.com/ANKer661.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Autograd Playground\n\nAutograd Playground is a simple implementation of automatic differentiation in Python \u0026 Numpy. This project allows users to create computation graphs, visualize them, and perform back propagation to understand how gradients flow between tensors.\n\n## Features\n\n- Simple `Tensor` class for creating and manipulating tensors\n- Support for basic mathematical operations: (element-wised `+`, `-`, `*`, `/`) and matrix multiplication\n- Automatic computation graph construction\n- Back-propagation for gradient computation\n- Visualization of computation graphs before and after back-propagation\n\n## Project Structure\n- `src`\n  - `tensor.py`: Contains the `Tensor` class implementation\n  - `operations.py`: Defines various mathematical operations (Add, Subtract, Multiply, etc.)\n  - `visualization.py`: Provides functions for visualizing computation graphs\n- `autograd-playground.ipynb`: Jupyter notebook with examples and explanations\n\n\n## Installation\n\n1. Clone this repository:\n```bash\ngit clone https://github.com/ANKer661/autograd-playground.git\ncd autograd-playground\n```\n\n2. Install required dependencies:\n```bash\npip install numpy matplotlib networkx\n```\n\nOr try out **Binder** for a quick start without any local installation. Click the badge below to launch the project in a Binder environment:\n\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/ANKer661/autograd-playground/main?labpath=autograd-playground.ipynb)\n\n## Usage\n\nThe main interface for this project is through the Jupyter notebook `autograd-playground.ipynb`. To run the notebook:\n\n1. Start Jupyter Notebook:\n```bash\njupyter notebook\n```\n\n2. Open `autograd-playground.ipynb` in your browser.\n\n3. Run the cells in the notebook to create tensors, build computation graphs, and visualize the results.\n\n## License\nThis project is licensed under the MIT License. See the LICENSE file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanker661%2Fautograd-playground","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fanker661%2Fautograd-playground","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanker661%2Fautograd-playground/lists"}