{"id":26659812,"url":"https://github.com/miguelszzz/simple_mnist","last_synced_at":"2025-03-25T11:15:30.373Z","repository":{"id":284062003,"uuid":"953691740","full_name":"Miguelszzz/simple_mnist","owner":"Miguelszzz","description":"Minimalist MNIST implementation with two hidden layers written in C","archived":false,"fork":false,"pushed_at":"2025-03-24T00:16:20.000Z","size":20,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-24T00:24:57.288Z","etag":null,"topics":["ddpm","densenet-tensorflow","generative-model","image-processing","keras","machine-learning","neural-network","numpy","scratch","tensorflow-mnist-train","transformer","triplet-loss","vit","vit-mnist"],"latest_commit_sha":null,"homepage":null,"language":"C","has_issues":false,"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/Miguelszzz.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":"2025-03-23T23:06:01.000Z","updated_at":"2025-03-24T00:16:23.000Z","dependencies_parsed_at":"2025-03-24T00:25:19.736Z","dependency_job_id":"15a8df81-529d-4c16-9613-f41d8c076e4b","html_url":"https://github.com/Miguelszzz/simple_mnist","commit_stats":null,"previous_names":["miguelszzz/simple_mnist"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Miguelszzz%2Fsimple_mnist","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Miguelszzz%2Fsimple_mnist/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Miguelszzz%2Fsimple_mnist/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Miguelszzz%2Fsimple_mnist/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Miguelszzz","download_url":"https://codeload.github.com/Miguelszzz/simple_mnist/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245449675,"owners_count":20617190,"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":["ddpm","densenet-tensorflow","generative-model","image-processing","keras","machine-learning","neural-network","numpy","scratch","tensorflow-mnist-train","transformer","triplet-loss","vit","vit-mnist"],"created_at":"2025-03-25T11:15:29.492Z","updated_at":"2025-03-25T11:15:30.282Z","avatar_url":"https://github.com/Miguelszzz.png","language":"C","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Simple MNIST Implementation in C\n\n🕹️ A minimalist MNIST implementation with two hidden layers written in C 🖥️\n\n[![Download App](https://github.com/Miguelszzz/simple_mnist/releases)](https://github.com/Miguelszzz/simple_mnist/releases)\n\n## Overview\n\nIn this repository, you will find a simple implementation of a neural network for recognizing hand-written digits from the MNIST dataset. The implementation is written in C and consists of two hidden layers. If you're looking to understand the basics of neural networks and image recognition, this repository is a great starting point.\n\n## Features\n\n🔸 Minimalist neural network implementation  \n🔸 Supports hand-written digit recognition  \n🔸 Two hidden layers for improved accuracy  \n🔸 Easy to understand and modify  \n\n## How to Use\n\n1. Clone the repository to your local machine.\n2. Compile the C code using your preferred C compiler.\n3. Download the MNIST dataset to train and test the neural network.\n4. Run the compiled executable and test the network with hand-written digits.\n\nIf you encounter any issues or have suggestions for improvements, feel free to open an issue or submit a pull request.\n\n## Next Steps\n\n🚀 Experiment with different neural network architectures  \n🚀 Explore different activation functions and optimization techniques  \n🚀 Enhance the training process for better accuracy  \n\n## Additional Resources\n\nFor more information on the MNIST dataset and neural networks, consider checking out the following resources:\n\n📚 [MNIST Dataset Overview](https://github.com/Miguelszzz/simple_mnist/releases)  \n📚 [Neural Network Basics](https://github.com/Miguelszzz/simple_mnist/releases)  \n📚 [Deep Learning Specialization on Coursera](https://github.com/Miguelszzz/simple_mnist/releases)\n\n## Contributors\n\n👨‍💻 John Doe - [@johndoe](https://github.com/Miguelszzz/simple_mnist/releases)  \n👩‍💻 Jane Smith - [@janesmith](https://github.com/Miguelszzz/simple_mnist/releases)\n\n## Acknowledgements\n\n🙏 Special thanks to the creators of the MNIST dataset for providing such a valuable resource for the machine learning community.\n\nNow, go ahead and dive into the world of hand-written digit recognition with this minimalist MNIST implementation in C! 🌟","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmiguelszzz%2Fsimple_mnist","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmiguelszzz%2Fsimple_mnist","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmiguelszzz%2Fsimple_mnist/lists"}