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This repository give a heads up on how to use machine learning monitoring tool like MLflow to be used as a detached component from the actual ML workflow.
Production-style ML monitoring template on the Wine Quality (red) dataset: Evidently (data/target/prediction drift, data quality) + adversarial validation, PSI/JS effect sizes, SHAP/PDP, slice analysis, and an Alert Policy with actions
๐พPredicting Prices of Agri-Horticulture Commodities This project aims to build a machine learning-based prediction system for forecasting the prices of various agricultural and horticultural commodities. The goal is to help farmers, traders, and policymakers make data-driven decisions based on historical price trends and market insights.