🌱 Crop Yield Prediction using Machine Learning
Implementation of Machine learning baseline for large-scale crop yield forecasting
Harness the power of machine learning to forecast rice and wheat crop yields per acre in India, aiming to empower smallholder farmers, combat poverty and malnutrition, utilizing data from Digital Green surveys to revolutionize agriculture and promote sustainable practices in the face of climate change for enhanced global food security.
A tool which is capable of making predictions of cereal and potato yields for districts of the Slovak Republic.
This project aims to design, develop and implement the training model by using different inputs data. The machine will able to learn the features and extract the crop yield from the data by using data mining and data science techniques.
Prediction of crop yields based on climate variables using machine learning algorithms
Crop Yield Prediction using various ML approaches - Random-Forest Regressor, Gradient-Boosting Regressor, Decision-Tree Regressor, Support-Vector Regressor
Machine Learning based Crop Yield Prediction
ML for crop yield prediction project that was part of my research at New Economic School
Explore our tools to make informed agricultural decisions.
A Mobile and Web application using which farmers can analyze the crops yield in the given set of environmental conditions
Crop Yield Prediction is a machine learning project that predicts crop yield using agricultural, soil, weather, and farming data. The final Linear Regression model is deployed as an interactive Streamlit web application.
Geospatial-AI corn yield forecasting for the U.S. Corn Belt. Team project fine-tuning NASA/IBM Prithvi-EO-2.0-600M with LoRA, fused with weather/soil/drought features and calibrated uncertainty cones. State-level RMSE ~3–5 bu/ac — competitive with USDA WASDE. CSU Geospatial AI Hackathon 2026.
Multiservice app with Crop Yield Prediction built using Django , React and Node.
🌾 CropCadet is a smart assistant for farmers and agri-enthusiasts, simplifying crop planning, monitoring, and decision-making through 🤖AI-powered insights.
AI-powered smart farming system for crop yield & price prediction, nutrient optimization with what-if analysis, and CV-based deficiency detection
Farmer assistant system VCET Hackathon 2k22
Ridge regression to forecast wheat yield variabilities for Brazil using observed and forecasted climate data.
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