{"id":26304447,"url":"https://github.com/luismisanve/mlp-trainer-examples","last_synced_at":"2026-02-23T16:31:47.638Z","repository":{"id":279423142,"uuid":"938760347","full_name":"LuisMiSanVe/MLP-Trainer-Examples","owner":"LuisMiSanVe","description":"Three MLP Trainer Examples compiled in a Jupyter Notebook","archived":false,"fork":false,"pushed_at":"2025-02-26T07:09:10.000Z","size":25,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-26T10:01:38.891Z","etag":null,"topics":["jupyter-notebook","matplotlib","mlp","numpy","python","torch"],"latest_commit_sha":null,"homepage":"","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/LuisMiSanVe.png","metadata":{"files":{"readme":"README.es.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,"zenodo":null}},"created_at":"2025-02-25T13:10:48.000Z","updated_at":"2025-05-13T09:33:29.000Z","dependencies_parsed_at":"2025-02-25T14:26:59.700Z","dependency_job_id":"8d9296b9-241d-470f-93e8-7e46c2dccf33","html_url":"https://github.com/LuisMiSanVe/MLP-Trainer-Examples","commit_stats":null,"previous_names":["luismisanve/mlp-trainer-examples"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/LuisMiSanVe/MLP-Trainer-Examples","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LuisMiSanVe%2FMLP-Trainer-Examples","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LuisMiSanVe%2FMLP-Trainer-Examples/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LuisMiSanVe%2FMLP-Trainer-Examples/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LuisMiSanVe%2FMLP-Trainer-Examples/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/LuisMiSanVe","download_url":"https://codeload.github.com/LuisMiSanVe/MLP-Trainer-Examples/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LuisMiSanVe%2FMLP-Trainer-Examples/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29748182,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-23T07:44:07.782Z","status":"ssl_error","status_checked_at":"2026-02-23T07:44:07.432Z","response_time":90,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["jupyter-notebook","matplotlib","mlp","numpy","python","torch"],"created_at":"2025-03-15T08:16:33.715Z","updated_at":"2026-02-23T16:31:47.608Z","avatar_url":"https://github.com/LuisMiSanVe.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003e [Ver en ingles/See in english](https://github.com/LuisMiSanVe/MLP-Trainer-Examples/blob/main/README.md)\n# 🧠 Ejemplos de Entrenador de MLP\n[![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](https://www.python.org/)\n[![image](https://img.shields.io/badge/Visual_Studio_Code-0078D4?style=for-the-badge\u0026logo=visual%20studio%20code\u0026logoColor=white)](https://code.visualstudio.com/)\n[![PyTorch](https://img.shields.io/badge/PyTorch-%23EE4C2C.svg?style=for-the-badge\u0026logo=PyTorch\u0026logoColor=white)](https://pytorch.org/)\n[![NumPy](https://img.shields.io/badge/numpy-%23013243.svg?style=for-the-badge\u0026logo=numpy\u0026logoColor=white)](https://numpy.org/)\n[![Jupyter Notebook](https://img.shields.io/badge/jupyter-%23FA0F00.svg?style=for-the-badge\u0026logo=jupyter\u0026logoColor=white)](https://jupyter.org/)\n\nUn Jupyter Notebook con tres Scripts de Python que entrenan Modelos de MLP con diferentes tipos de datos, funciones y resultados.\n\n## 📋 Prerequisitos\nAntes que nada, necesitas poder abrir/ejecutar estos scripts, para ello, puedes o bien usar la consola o un IDE como [Visual Studio Code](https://code.visualstudio.com/). Estos son los pasos para hacerlo de ambas maneras.\n- **Consola**:\n  Instala la ultima version de [Python](https://www.python.org/).\n  Entonces, abre un terminal e instala Jupyter Notebook con el siguiente comando:\n  ```\n  pip install jupyter\n  ```\n  Si falla o tienes una version diferente de Python:\n  ```\n  py -m pip install jupyter\n  ```\n- **VS Code**:\n  Ve al Marketplace e instala las extensiones de [Python](https://marketplace.visualstudio.com/items?itemName=ms-python.python) y [Jupyter](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter).\n\nPara ejecutar los scripts, tanto en consola como en un IDE, **debes** instalar las siguientes dependencias en una terminal:\n```\npip install torch matplotlib numpy\n```\nSi falla o tienes una version diferente de Python:\n```\npy -m pip install torch matplotlib numpy\n```\n\n## 🛠️ Instalación\nAbre el Jupyter Notebook con VS Code o con su aplicación web ejecutando este comando:\n```\njupyter notebook\n```\nSi falla o tienes una version diferente de Python:\n```\npy -m jupyter notebook\n```\nEntonces, la app se abrirá sola en tu navegador por defecto.\n\n## 🚀 Explicación de uso del proyecto\nSigue la guía y ejecuta las Células de Código Python en el Jupyter Notebook para entrenar y ver los resultados de los Modelos MLP.\n\nLos tres scripts generan un Modelo MLP cada uno con sus funcionalidades y tipos de datos.\n\nPara probar a cambiar los resultados, ajusta los parametros del Modelo y los ajustes del entrenamiento (marcado en los comentarios).\n\nSu funcionalidad está explicada en cada Script de Python.\n\n## 💻 Tecnologías usadas\n- Lenguaje de programación: [Python](https://www.python.org/) (3.13.2)\n- Librerías:\n  - [torch](https://pypi.org/project/torch/) (2.6.0)\n  - [numpy](https://numpy.org/) (2.2.0)\n  - [matplotlib](https://matplotlib.org/) (3.10)\n- Otros:\n  - [Jupyter](https://jupyter.org/)\n  - [VS Code Python Extension](https://marketplace.visualstudio.com/items?itemName=ms-python.python)\n  - [VS Code Jupyter Extension](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter)\n- IDE Recomendado: [VS Code](https://code.visualstudio.com/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fluismisanve%2Fmlp-trainer-examples","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fluismisanve%2Fmlp-trainer-examples","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fluismisanve%2Fmlp-trainer-examples/lists"}