Dependency Management and Reproducibility
Ensuring experiment reproducibility
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My ML project needs to be reproducible across different environments. Generate the complete configuration to ensure reproducibility: random seed management, a requirements.txt file with pinned versions, environment variable setup, and a Makefile with commands to reproduce the experiments.
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Ajoutez un fichier `environment.yml` (Conda) pour capturer à la fois les packages Python et les bibliothèques système (CUDA, etc.) — plus robuste que `requirements.txt` seul, surtout si le projet dépend de binaires. Utilisez `conda env export > environment.yml` après installation.
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