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Simple Logistic Regression using Matrix Factorization in PyTorch

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logistic-mf-pytorch

Simple Logistic Regression using Matrix Factorization in PyTorch

This is a simple Python project that implements logistic regression using matrix factorization in PyTorch. It can be used for collaborative filtering tasks such as recommendation systems.

Requirements

  • Python 3.6 or higher
  • PyTorch 1.8 or higher
  • Numpy
  • Pandas

Usage

  • Clone this repository to your local machine.
  • logistic_mf.py contains the core logic to train the model on a toy dataset (tiny_data).
  • You can also use logistic_mf_helper.ipynb or test_logistic_mf.ipynb to interact with the model in a Jupyter notebook.
  • You can modify the hyperparameters and the dataset in the logistic_mf.py file.

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Simple Logistic Regression using Matrix Factorization in PyTorch

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