{"id":20663641,"url":"https://github.com/abrahamkoloboe27/regression-application-streamlit","last_synced_at":"2025-08-24T09:34:02.983Z","repository":{"id":246890780,"uuid":"824244957","full_name":"abrahamkoloboe27/Regression-Application-Streamlit","owner":"abrahamkoloboe27","description":"Lien de l'application","archived":false,"fork":false,"pushed_at":"2024-07-05T15:14:31.000Z","size":1233,"stargazers_count":2,"open_issues_count":0,"forks_count":3,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-27T01:35:31.830Z","etag":null,"topics":["data-processing","fine-tuning","machine-learning","machine-learning-algorithms","pycaret","python","regression-models","streamlit","training-model","visualization"],"latest_commit_sha":null,"homepage":"https://regression-application-app-zach27.streamlit.app/","language":"Python","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/abrahamkoloboe27.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":"2024-07-04T17:08:58.000Z","updated_at":"2024-12-27T14:58:55.000Z","dependencies_parsed_at":"2024-07-05T19:32:03.512Z","dependency_job_id":"b02b8c59-0272-441e-858f-33d98e3eb72f","html_url":"https://github.com/abrahamkoloboe27/Regression-Application-Streamlit","commit_stats":null,"previous_names":["abrahamkoloboe27/regression-application-streamlit"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abrahamkoloboe27%2FRegression-Application-Streamlit","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abrahamkoloboe27%2FRegression-Application-Streamlit/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abrahamkoloboe27%2FRegression-Application-Streamlit/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abrahamkoloboe27%2FRegression-Application-Streamlit/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/abrahamkoloboe27","download_url":"https://codeload.github.com/abrahamkoloboe27/Regression-Application-Streamlit/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248695481,"owners_count":21146956,"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":["data-processing","fine-tuning","machine-learning","machine-learning-algorithms","pycaret","python","regression-models","streamlit","training-model","visualization"],"created_at":"2024-11-16T19:19:02.845Z","updated_at":"2025-04-13T10:10:30.974Z","avatar_url":"https://github.com/abrahamkoloboe27.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Regression Application with Streamlit and PyCaret\n\nWelcome to the Regression Application repository! This application provides an intuitive interface for performing end-to-end regression analysis using Streamlit and PyCaret. It guides the user through various steps including data import, preprocessing, model training, fine-tuning, visualization, and final model deployment.\n\n## 📋 Table of Contents\n- [Features](#features)\n- [Installation](#installation)\n- [Usage](#usage)\n- [Pages Overview](#pages-overview)\n- [Contributing](#contributing)\n- [License](#license)\n- [Contact](#contact)\n\n## ✨ Features\n- 📥 **Data Import**: Upload your own dataset or use predefined datasets.\n- 🔧 **Setup**: Configure preprocessing steps and training parameters.\n- 🤖 **Train Models**: Train multiple regression models and compare their performance.\n- 🔨 **Fine-Tuning**: Optimize model performance with various fine-tuning techniques.\n- 📈 **Regression Plots**: Visualize model performance through interactive plots.\n- 🔮 **Make Predictions**: Use the trained models to make predictions.\n- 💾 **Finalization and Saving**: Save the best performing model for deployment.\n\n## ⚙️ Installation\nTo run this application locally, follow these steps:\n\n1. **Clone the repository:**\n    ```sh\n    git clone https://github.com/abrahamkoloboe27/Regression-Application-Streamlit.git\n    ```\n2. **Navigate to the project directory:**\n    ```sh\n    cd Regression-Application-Streamlit\n    ```\n3. **Install the required packages:**\n    ```sh\n    pip install -r requirements.txt\n    ```\n\n## 🚀 Usage\nTo start the application, run the following command:\n```sh\nstreamlit run app.py\n```\n\nOnce the application is running, you can access it in your web browser at `http://localhost:8501`.\n\n## 📄 Pages Overview\n\n1. **Home Page** 📥:\n    - Import your dataset and select the target variable.\n\n2. **Setup** 🔧:\n    - Configure data preprocessing and training settings.\n\n3. **Train Models** 🤖:\n    - Train multiple regression models and compare their performance.\n\n4. **Fine-Tuning** 🔨:\n    - Optimize the selected models using fine-tuning techniques.\n\n5. **Regression Plots** 📈:\n    - Visualize and compare the performance of trained models through various plots.\n\n6. **Make Predictions** 🔮:\n    - Use the trained models to make predictions on new data.\n\n7. **Finalization and Saving** 💾:\n    - Finalize and save the best model for deployment.\n\n## 🤝 Contributing\nContributions are welcome! If you have any ideas, suggestions, or bug reports, feel free to open an issue or submit a pull request.\n\n## 📜 License\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## 📞 Contact\nIf you have any questions or feedback, feel free to reach out to me:\n\n- **Email**: abklb27@gmail.com\n- **LinkedIn**: [Abraham Z. KOLOBOE](https://www.linkedin.com/in/abraham-zacharie-koloboe-data-science-ia-generative-llms-machine-learning/)\n\n---\n\nThank you for using this regression application! If you find it useful, please consider giving the repository a star ⭐.\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabrahamkoloboe27%2Fregression-application-streamlit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabrahamkoloboe27%2Fregression-application-streamlit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabrahamkoloboe27%2Fregression-application-streamlit/lists"}