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This project is an end-to-end machine learning solution for predicting blueberry yield based on various environmental and biological factors. Using Python and Flask for the back-end and Bootstrap for the front-end, it incorporates data ingestion, transformation, model training, and prediction stages. The prediction model is powered by CatBoost Algo
Interconnect seeks to forecast customer churn by analyzing package choices and contracts. If a customer plans to leave, they're offered unique codes and special packages to foster loyalty.