Als

* This nascent repository, utilizing Jupyter Notebooks, needs immediate implementation to realize the proposed collaborative filtering data science project. * The misleadingly high architecture score (70%) stems from zero code; define robust MLOps patterns immediately for future production readiness. * Future model implementation requires migrating core ALS logic from notebooks into testable, production-grade Python modules for better deployment. * Establish rigorous dependency management and clear data versioning protocols, which are crucially salting the success of iterative model development. * Ensure `.gitignore` is properly configured to exclude large data artifacts and sensitive environment outputs inherent in the Jupyter structure.