MashedP/dlip-pytorch-DL-good-practises

This project offers a template and guidelines for structuring deep learning research and development projects. It helps researchers and data scientists organize their code, manage experimental configurations, and track results effectively. By providing a clear project structure and integrating tools like Hydra and MLflow, it takes unstructured research ideas and code, and helps produce well-organized, reproducible deep learning experiments and trained models.