#
ials
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Recipe-driven recommender systems on irspack — one YAML = one model = one recommendation API. Train writes a signed artifact; serve mounts it with hot-swap. Single binary, no database.
python recommendations machine-learning personalization collaborative-filtering matrix-factorization bpr recommender recommendation-system recsys recommendation-engine recommender-system implicit-feedback serving mlops fastapi optuna ials recommendation-api irspack
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Sep 26, 2026 - Python
Music recommender on Yandex's Yambda dataset: time-based validation, repeat-aware evaluation, time-decay baselines, iALS and a two-stage CatBoost ranker.
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Oct 11, 2026 - Jupyter Notebook
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