Metadata-Version: 2.3
Name: isne-recommendation
Version: 0.1.3
Summary: The recommendation system aims to suggest the best suitable courses for learners who have taken at least one course.
Project-URL: Homepage, https://github.com/startg2545/recommendation-system
Project-URL: Issues, https://github.com/startg2545/recommendation-system/issues
Author-email: Newin Yamaguchi <newin_yamaguchi@cmu.ac.th>
License-File: LICENSE
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.8
Requires-Dist: fuzzywuzzy==0.18.0
Requires-Dist: joblib==1.3.2
Requires-Dist: levenshtein==0.25.0
Requires-Dist: numpy==1.26.4
Requires-Dist: openpyxl==3.1.2
Requires-Dist: pandas==1.5.3
Requires-Dist: python-dateutil==2.9.0.post0
Requires-Dist: python-levenshtein==0.25.0
Requires-Dist: pytz==2024.1
Requires-Dist: rapidfuzz==3.6.2
Requires-Dist: scikit-learn==1.4.1.post1
Requires-Dist: scipy==1.12.0
Requires-Dist: six==1.16.0
Requires-Dist: threadpoolctl==3.3.0
Requires-Dist: tzdata==2024.1
Description-Content-Type: text/markdown

# Recommendation System

The recommendation system aims to suggest the best suitable courses for learners who have taken at least one course.

## Table of Contents

- [Installation](#installation)
- [Usage](#tutorial)
- [Contributing](#contributors)
- [License](#license)

## Installation

To install and set up the project, you can use the following command:

```[PowerShell]
pip install isne-recommendation
```

For detailed instructions on how to install the Study Focus Recommendation System, please navigate to our installation guide on [installation](https://docs.isne-recommendation.com/get-started/installation). Follow the step-by-step instructions to set up the system on your machine and start enhancing your study experience today.

## Tutorial

After installation is successful, you can now import these functions from an isne_recommendation package:

```[PowerShell]
from isne_recommendation import TfidfLinearKernel, FeatureRatingsKNN, Hybrid
```

Are you seeking to unravel the mysteries behind recommendation systems? Look no further! Dive into the comprehensive guide available at [tutorial](https://docs.isne-recommendation.com/get-started/tutorial).

## Contributors

Check out our [contribution guidelines](https://docs.isne-recommendation.com/contributors) to learn how you can get involved. Whether it's coding, documentation, testing, or providing feedback, every contribution makes a difference and helps us create a better tool for students worldwide.

## License

**License:** MIT

Please refer to the [LICENSE](https://docs.isne-recommendation.com/license) for more details.
