{"id":27647211,"url":"https://github.com/techiescamp/mlops","last_synced_at":"2025-04-24T01:49:04.457Z","repository":{"id":274923564,"uuid":"919257913","full_name":"techiescamp/mlops","owner":"techiescamp","description":" MLOPS Projects","archived":false,"fork":false,"pushed_at":"2025-04-16T22:08:48.000Z","size":5952,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-24T01:48:55.788Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"JavaScript","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/techiescamp.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,"zenodo":null}},"created_at":"2025-01-20T04:01:37.000Z","updated_at":"2025-04-16T22:08:55.000Z","dependencies_parsed_at":"2025-02-26T08:20:00.078Z","dependency_job_id":"7cc36be3-eafc-4d3d-a680-cef3c8a49219","html_url":"https://github.com/techiescamp/mlops","commit_stats":null,"previous_names":["techiescamp/mlops"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/techiescamp%2Fmlops","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/techiescamp%2Fmlops/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/techiescamp%2Fmlops/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/techiescamp%2Fmlops/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/techiescamp","download_url":"https://codeload.github.com/techiescamp/mlops/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":250546022,"owners_count":21448255,"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":[],"created_at":"2025-04-24T01:49:03.667Z","updated_at":"2025-04-24T01:49:04.446Z","avatar_url":"https://github.com/techiescamp.png","language":"JavaScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"# MLOPS Projects\n----------------------------------------\n\n## OVerview\n\nThis repository provides a comprehensive approach to Machine Learning Operations (MLOps), integrating machine learning models into production with automation, monitoring, and scalability. It covers best practices, CI/CD pipelines, model versioning, and deployment strategies.\n\n## Projects\n\nThis repository includes multiple MLOps projects, each focusing on different aspects of machine learning model development, deployment, and monitoring. The projects are structured as follows:\n\n### **Employee Attrition Prediction**\n\n        - Uses Logistic Regression for predicting employee attrition.\n        - Implements Flask for web-based model interaction.\n        - Features automated data preprocessing, model training, and deployment using Docker and Kubernetes.\n\n### **LLM-Based Simple models using Hugging Face**\n\n        - Built simple LLM project using Hugging Face's open source models on\n            - text summarization, \n            - text generation, \n            - sentiment-analysis, \n            - question-answering and \n            - table question-answering models\n\n        - Deploys via `React` (frontend) and `Node.js,Express.js` (backend) for seamless user experience.\n\n## Installation \u0026 Setup\n\n**Prerequisites**\n\n    - Python 3.x\n    - Docker \u0026 Kubernetes (Optional for Deployment)\n\n**Steps**\n\n    1. Clone the repository\n    ```\n    git clone https://github.com/techiescamp/mlops.git\n    cd mlops\n    ```\n\n    2.  a virtual environment (Recommended)\n    ```\n    python -m venv venv\n    source venv/bin/activate  # For macOS/Linux\n    venv\\Scripts\\activate     # For Windows\n    ```\n\n    3. Install dependencies (if requirements.txt exists)\n    ```\n    pip install -r requirements.txt\n    ```\n\n    Go to directory on which project you needed and start working on it.\n\n## Future Enhancement\n\n    - Automated ML Pipelines using DVC \u0026 MLflow.\n    - Continuous Integration \u0026 Deployment (CI/CD) with GitHub Actions.\n    - Model Versioning and tracking experiments.\n    - Cloud Deployment with Docker \u0026 Kubernetes.\n    - Monitoring \u0026 Logging with Prometheus \u0026 Grafana.\n\n\n## License\n\nThis project is open-source and available under the MIT License.\n**\u0026copy; www.techiescamp.com/**\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftechiescamp%2Fmlops","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftechiescamp%2Fmlops","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftechiescamp%2Fmlops/lists"}