{"id":28879629,"url":"https://github.com/pacatro/ucorecsys","last_synced_at":"2026-04-20T13:32:15.927Z","repository":{"id":297527444,"uuid":"937722545","full_name":"Pacatro/UcoRecSys","owner":"Pacatro","description":"Application of Recommendation Systems in Educational Environments","archived":false,"fork":false,"pushed_at":"2025-09-26T00:58:42.000Z","size":27996,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-10-26T03:41:39.870Z","etag":null,"topics":["ai","bash","csv","deep-learning","jupyter-notebook","machine-learning","python","pytorch","pytorch-lightning","recommender-system","surprise","tensorboard","toml","torchmetrics","uv"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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is part of the Bachelor’s Thesis (TFG) by Francisco de Paula Algar Muñoz at the University of Córdoba (UCO), titled: **_Application of Recommendation Systems in Educational Environments_** ([PDF](./Memoria_TFG.pdf)).\n\n\u003e [!NOTE]  \n\u003e Most of the project is written in Spanish, only this repository has been translated into English.\n\nThe goal of this project is to develop a recommendation system for e-learning based on a benchmark dataset, allowing evaluation of its performance compared to previous models.\n\n## Usage\n\n```bash\nucorecsys [-h] (-i MODEL_PATH | -t | -e | -s | -st) [-ds {mars,itm}] [-cv {kfold,loo}]\n                 [--top_k TOP_K] [--epochs EPOCHS] [--batch_size BATCH_SIZE] [--output_model MODEL_OUT]\n                 [-lr LR] [-k K_SPLITS] [--seeds SEEDS] [-p] [-v]\n```\n\n### Options\n\n```bash\n-h, --help            Show this help message and exit\n-i MODEL_PATH, --inference MODEL_PATH\n                      Run inference on a trained model (provide path to model file).\n-t, --train           Train the model.\n-e, --eval            Evaluate the model.\n-s, --surprise        Run Surprise evaluation.\n-st, --stats_test     Run statistical tests (default: False).\n\nCommon Options:\n  -ds {mars,itm}, --dataset {mars,itm}\n                        Dataset to use (default: mars).\n  -cv {kfold,loo}, --cvtype {kfold,loo}\n                        Cross-validation type (default: kfold).\n  --top_k TOP_K         Top-k value for ranking metrics (default: 10).\n\nTraining Options:\n  --epochs EPOCHS       Number of training epochs (default: 50).\n  --batch_size BATCH_SIZE\n                        Training batch size (default: 128).\n  --output_model MODEL_OUT\n                        Path to save the trained model (default: model.pt).\n  -lr LR                Learning rate (default: 0.001).\n\nEvaluation Options:\n  -k K_SPLITS, --k_splits K_SPLITS\n                        Number of CV splits (default: 5).\n  --seeds SEEDS         Random seeds (default: [0, 1, 42]).\n\nMiscellaneous Options:\n  -p, --plot            Generate plots.\n  -v, --verbose         Enable verbose output.\n```\n\n## Getting Started\n\n\u003e [!NOTE]  \n\u003e To run this project, you need to have the [`uv`](https://docs.astral.sh/uv/) package manager installed.\n\nFollow these steps to run the project:\n\n1. **Clone the repository**\n\n   ```bash\n   git clone https://github.com/Pacatro/UcoRecSys.git\n   cd UcoRecSys\n   ```\n\n2. **Install dependencies and create a virtual environment**\n\n   ```bash\n   uv sync --extra cpu # For CPU\n   uv sync --extra cu128 # For CUDA 12.8\n   ```\n\n3. **Run the project**\n\n   ```bash\n   uv run src/main.py -h\n   ```\n\n## Examples\n\n- Train the model on the MARS dataset for 10 epochs, generating a Top-15 recommendation list and saving the model as `tfg.pt`:\n\n  ```bash\n  uv run src/main.py -t -ds mars --epochs 10 --top_k 15 --output_model tfg.pt\n  ```\n\n- Run inference using the previously trained model:\n\n  ```bash\n  uv run src/main.py -i tfg.pt\n  ```\n\n## Author\n\n[**Francisco de Paula Algar Muñoz**](https://github.com/Pacatro)\n\n## Advisors\n\n**Amelia Zafra Gómez**  \n**Cristóbal Romero Morales**\n\n## License\n\n[**MIT**](https://opensource.org/license/mit) - Created by [**Paco Algar Muñoz**](https://github.com/Pacatro)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpacatro%2Fucorecsys","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpacatro%2Fucorecsys","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpacatro%2Fucorecsys/lists"}