Skip to content

This is a Streamlit application that provides personalized course recommendations based on user preferences. The app allows users to select courses they have audited or completed, trains a recommendation model, and generates recommendations for new courses.

License

Notifications You must be signed in to change notification settings

muhammadadilnaeem/Course-Recommender-App

Repository files navigation

Course Recommender App

This is a Streamlit application that provides personalized course recommendations based on user preferences. The app allows users to select courses they have audited or completed, trains a recommendation model, and generates recommendations for new courses.

course.recomender.mp4

Features

  • Interactive course selection using a dynamic table
  • Model training with feedback at each step
  • Personalized course recommendations
  • Enhanced UI with emojis, colored headings, and central alignment for a better user experience

Installation

  1. Clone the repository:

    git clone https://github.com/muhammadadilnaeem/Course-Recommender-App.git
    cd Course-Recommender-App
  2. Create and activate a virtual environment:

    python -m venv st_env
    st_env\Scripts\activate
  3. Install the required packages:

    pip install -r requirements.txt
  4. Ensure you have the datasets in the data folder:

    Course-Recommender-App/
    ├── data/
    │   ├── ratings.csv
    │   ├── sim.csv
    │   ├── course_processed.csv
    │   └── courses_bows.csv
    ├── backend.py
    ├── recommender_app.py
    └── requirements.txt
    

Running the App

  1. Run the Streamlit app:

    streamlit run recommender_app.py
  2. Open your web browser and navigate to:

    http://localhost:8501
    

Code Structure

  • backend.py: Contains functions for loading datasets, adding new ratings, and generating course recommendations.
  • recommender_app.py: The main Streamlit app file. It includes the UI components and integrates the backend functions.

Usage

  1. Select courses you have audited or completed.
  2. Train the model using the sidebar options.
  3. Generate course recommendations by clicking the "Recommend New Courses" button.

Customization

  • The app uses emojis and colored headings to enhance the user experience.
  • Advanced HTML and CSS are used to style the app.

Contributing

  1. Fork the repository
  2. Create a new branch
  3. Make your changes
  4. Submit a pull request

License

This project is licensed under the MIT License.

Contact

For any issues or feature requests, please open an issue on this repository or contact me directly at madilnaeem0@gmail.com.


About

This is a Streamlit application that provides personalized course recommendations based on user preferences. The app allows users to select courses they have audited or completed, trains a recommendation model, and generates recommendations for new courses.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages