{"id":19774273,"url":"https://github.com/ganesh2409/course-recommendation-system","last_synced_at":"2026-04-12T12:32:20.768Z","repository":{"id":245599042,"uuid":"818715467","full_name":"Ganesh2409/Course-Recommendation-System","owner":"Ganesh2409","description":"🚀 Course Recommendation System is a machine learning-powered web application designed to recommend similar courses from Coursera's vast dataset of over 3,000 courses. Built using Python, Scikit-learn, and Streamlit, the app preprocesses course data, applies text vectorization, and leverages cosine similarity to offer personalized recommendations. ","archived":false,"fork":false,"pushed_at":"2024-10-10T17:28:44.000Z","size":78936,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-11T01:26:13.061Z","etag":null,"topics":["cosine-similarity","data-science","docker","machine-learning","nlp","python","recommendation-system","streamlit-webapp","text-vectorization"],"latest_commit_sha":null,"homepage":"https://course-recommendation-system-wqs3sudhu9m28yjpfbuvwd.streamlit.app/","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/Ganesh2409.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":"2024-06-22T16:42:11.000Z","updated_at":"2024-10-10T17:28:49.000Z","dependencies_parsed_at":"2025-01-11T01:25:15.908Z","dependency_job_id":"f830f8ff-346d-4920-b61e-b52b164df96a","html_url":"https://github.com/Ganesh2409/Course-Recommendation-System","commit_stats":null,"previous_names":["ganesh2409/course-recommendation-system-","ganesh2409/course-recommendation-system"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ganesh2409%2FCourse-Recommendation-System","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ganesh2409%2FCourse-Recommendation-System/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ganesh2409%2FCourse-Recommendation-System/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ganesh2409%2FCourse-Recommendation-System/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Ganesh2409","download_url":"https://codeload.github.com/Ganesh2409/Course-Recommendation-System/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241105052,"owners_count":19910560,"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":["cosine-similarity","data-science","docker","machine-learning","nlp","python","recommendation-system","streamlit-webapp","text-vectorization"],"created_at":"2024-11-12T05:12:23.000Z","updated_at":"2026-04-12T12:32:15.736Z","avatar_url":"https://github.com/Ganesh2409.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Course Recommendation System 🚀\n\nA Dockerized machine learning-based web application that recommends similar courses from a dataset of over 3,000 courses on Coursera. The app uses text vectorization and cosine similarity to provide personalized course recommendations based on user input.\n\n## Features 🔥\n- Data preprocessing and cleaning\n- Vectorization of course descriptions and skills using `sklearn`\n- Cosine similarity-based course recommendation engine\n- Interactive web interface built with `Streamlit`\n- Fully Dockerized for easy deployment\n\n## Table of Contents 📑\n- [Installation](#installation )\n- [Project Structure](#project-structure)\n- [Usage](#usage)\n- [Docker](#docker)\n- [Contributing](#contributing)\n- [Contact](#contact)\n\n## Installation 🛠️\n\nTo run the project locally, follow these steps:\n\n1. Clone the repository:\n   ```bash\n   git clone https://github.com/ganesh2409/Course-Recommendation-System.git\n   cd Course-Recommendation-System\n   ```\n\n2. Create and activate a virtual environment (optional but recommended):\n   ```bash\n   python -m venv env\n   source env/bin/activate  # Mac/Linux\n   .\\env\\Scripts\\activate   # Windows\n   ```\n\n3. Install the required dependencies:\n   ```bash\n   pip install -r requirements.txt\n   ```\n## Project Structure 🗂️\n\n```\nCourse-Recommendation-System/\n├── Data/\n│   └── Coursera.csv                                  # Coursera dataset\n├── models/\n│   ├── course_list.pkl                               # Precomputed similarity matrix\n│   └── courses.pkl                                   # Processed course list\n├── main.py                                           # Streamlit app script\n├── CourseRecommendationSystem.py                     # Data preprocessing and model training script \n├── requirements.txt                                  # Python dependencies\n├── Dockerfile                                        # Docker configuration\n└── README.md                                         # Project README file\n```\n\n## Usage ⚙️\n\n1. **Run the preprocessing and model training script**:\n   ```bash\n   python CourseRecommendationSystem.py\n   ```\n\n2. **Run the Streamlit application**:\n   ```bash\n   streamlit run main.py\n   ```\n\n3. **Navigate to the local URL (http://localhost:8501)** to use the web app.\n\n## Docker Hub 🐳\n\nTo directly use the project from Docker Hub\n\n1. **Pull the pre-built Docker image**:\n   ```bash\n   docker pull ganeshpinnamaneni/course-recommendation-system:latest\n   ```\n\n2. **Run the Docker container**:\n   ```bash\n   docker run -p 8501:8501 ganeshpinnamaneni/course-recommendation-system:latest\n   ```\n\n3. **Access the web app** at [http://localhost:8501](http://localhost:8501).\n\n\n## Contributing 🤝\n\nWe welcome contributions to improve the Course Recommendation System. Here's how you can contribute:\n\n1. Fork the repository.\n2. Create a new branch (`git checkout -b feature-branch`).\n3. Commit your changes (`git commit -m 'Add new feature'`).\n4. Push to the branch (`git push origin feature-branch`).\n5. Create a Pull Request.\n\n## Contact 📧\n\nFor any questions or feedback, feel free to reach out:\n\n- **Ganesh Chowdhary P** – pinnamaneniganesh24@gmail.com\n- GitHub: [Ganesh Chowdhary P](https://github.com/ganesh2409)\n```\nMade with ❤️ ( ͡• ͜ʖ ͡• ) Follow for more  ... :) \n``` \n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fganesh2409%2Fcourse-recommendation-system","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fganesh2409%2Fcourse-recommendation-system","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fganesh2409%2Fcourse-recommendation-system/lists"}