recohut 0.0.8

A python library for building recommender systems.

recohut

a python library for building recommender systems.
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About The Project

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Built With

• Python
• PyTorch
• Numpy
• Pandas
• nbdev
• Jupyter

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Getting Started

To get a local copy up and running follow these simple example steps.

Prerequisites

• pytorch

  pip install torch
  

Installation

pip install recohut

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Usage

# import the required modules
import recohut
from recohut.datasets import MovieLens
from recohut.models import MatrixFactorization

# define the data and model
data = MovieLens(version='100k', download=True)
model = MatrixFactorization()

# train the matrix factorization model
model.train(data)

# evaluate the model
model.evaluate(metrics=['MRR','HR'])

For more examples, please refer to the Documentation and Tutorials.

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Roadmap

• [] RecSys Model Deployment and MLOps features
• [] RL agents and environment specific to recommender systems
• [] Visualization utilities and EDA

See the open issues for a full list of proposed features (and known issues).

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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License

Distributed under the MIT License. See LICENSE.txt for more information.

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Contact

Your Name - Sparsh A.

Project Link: https://github.com/RecoHut-Projects/recohut

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Acknowledgments

• nbdev team for providing supporting tools to build this library.
• colab team for providing running VMs instances for development and testing.

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