Caidin is a Python library that provides a collection of recommendation algorithms and utilities for building recommendation systems. It aims to simplify the process of creating and experimenting with recommendation engines in various domains.
- Implementation of collaborative filtering, matrix factorization, and content-based recommendation algorithms.
- Utility functions for data loading, preprocessing, and evaluation.
- Clear and customizable model structures for users and recommenders.
- Well-documented codebase with usage examples.
You can install Caidin using pip:
pip install caidin
For detailed installation instructions and requirements, please refer to the Installation Guide.
For detailed usage instructions, API references, and example code, please refer to the Documentation.
Check out the Examples directory for step-by-step examples demonstrating how to use Caidin for building recommendation systems.
We welcome contributions from the community! Please refer to the Contributing Guidelines for information on how to get started, code style, and the contribution process.
Please review our Code of Conduct that outlines the behavior we expect from all contributors and users of the project.
This project is licensed under the MIT License.