{"id":23024504,"url":"https://github.com/derrickbaruga7/pytorch-machine-learning","last_synced_at":"2026-05-05T07:32:22.276Z","repository":{"id":250031207,"uuid":"833301855","full_name":"derrickbaruga7/Pytorch-Machine-Learning","owner":"derrickbaruga7","description":"A repository showcasing the creation and testing of production-ready machine learning models, emphasizing data processing optimization, pipeline efficiency, and rigorous testing for deployment.","archived":false,"fork":false,"pushed_at":"2025-01-07T20:59:28.000Z","size":340,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-02T19:47:05.138Z","etag":null,"topics":["data-science","machine-learning","marketing","predictive-modeling","pytorch"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/derrickbaruga7.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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":"2024-07-24T18:57:28.000Z","updated_at":"2025-01-07T20:59:31.000Z","dependencies_parsed_at":"2024-07-24T20:46:12.502Z","dependency_job_id":"7b400af6-362b-4592-a4d6-b8b62e118b14","html_url":"https://github.com/derrickbaruga7/Pytorch-Machine-Learning","commit_stats":null,"previous_names":["derrickbaruga7/pytorch-machine-learning"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/derrickbaruga7/Pytorch-Machine-Learning","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/derrickbaruga7%2FPytorch-Machine-Learning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/derrickbaruga7%2FPytorch-Machine-Learning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/derrickbaruga7%2FPytorch-Machine-Learning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/derrickbaruga7%2FPytorch-Machine-Learning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/derrickbaruga7","download_url":"https://codeload.github.com/derrickbaruga7/Pytorch-Machine-Learning/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/derrickbaruga7%2FPytorch-Machine-Learning/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32640533,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-04T10:08:07.713Z","status":"online","status_checked_at":"2026-05-05T02:00:06.033Z","response_time":54,"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":["data-science","machine-learning","marketing","predictive-modeling","pytorch"],"created_at":"2024-12-15T13:19:14.396Z","updated_at":"2026-05-05T07:32:22.260Z","avatar_url":"https://github.com/derrickbaruga7.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Machine Learning Model Development and Testing\n\nThis repository contains the code and workflow for creating, testing, and deploying machine learning models. The focus is on optimizing model accuracy, improving data processing pipelines, and ensuring robust deployment of production-ready systems.\n\n## Features\n\n• Model Development: Creating machine learning pipelines using advanced algorithms (e.g., LSTMs).\n\n• Data Ingestion: Optimized data pipelines for faster processing of large datasets.\n\n• Testing \u0026 Validation: Comprehensive quality assurance to ensure high model performance and pre-deployment reliability.\n\n• Deployment: End-to-end deployment processes for scalable and efficient machine learning solutions.\n\n## Technologies Used\n\n• Programming: Python\n\n• Machine Learning Libraries: Scikit-learn, TensorFlow, PyTorch\n\n• Data Processing: Pandas, NumPy\n\n• Deployment: Docker, Flask/FastAPI\n\n• Version Control: Git\n\n## How to Use\n\nClone this repository:\n\n\tgit clone https://github.com/your-username/ml-model-development.git\n\n\nNavigate to the project directory:\n\n\tcd ml-model-development\n\n\nInstall dependencies:\n\n\tpip install -r requirements.txt\n\n\nRun the Jupyter Notebook (model 2.ipynb) for training and testing the machine learning model.\n\n## Future Improvements\n\n• Expansion to support real-time predictions.\n• Enhanced testing workflows with more advanced statistical validations.\n• Integration with cloud services for automated ML.\n\nA repository showcasing the creation and testing of production-ready machine learning models, emphasizing data processing optimization, pipeline efficiency, and rigorous testing for deployment.\n\nLet me know if you’d like to customize further or add sections like examples of model outputs or diagrams!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fderrickbaruga7%2Fpytorch-machine-learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fderrickbaruga7%2Fpytorch-machine-learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fderrickbaruga7%2Fpytorch-machine-learning/lists"}