Predictive analytics can transform how businesses address quality challenges. In my Post-Harvest Quality Project, I used Python to build a model that reduced waste by 30%. Here’s how:
Data Collection: Analyzed quality parameters using HPLC and spectrophotometry.
Model Building: Built a predictive model in Python to forecast spoilage trends.
Outcome: Enhanced shelf life prediction accuracy by 25%.
Predictive modeling isn't just about reducing waste—it’s about creating efficient systems. Explore my Project to see the full story.
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