Forecasts regional crop yield from weather, soil and historical harvest data.
This is placeholder project copy — swap in your own write-up when you're ready.
A regression model that combines historical yield records with weather and soil readings to forecast next season's crop yield for a given district, wrapped in a small Flask API for other tools to call.
Demo highlights (edit freely): - Feature set covering rainfall, temperature and soil composition - Model comparison across linear, tree-based and gradient-boosted regressors - REST endpoint returning a yield estimate with a confidence range