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Crop Yield Prediction with ML Techniques by dolumohan782 is a document available to read on EtoBox.

The project report focuses on developing a machine learning-based system for predicting crop yields, utilizing Decision Tree Regression to analyze agricultural and climatic factors. The system achieves a predictive accuracy of 0.87 and includes a user-friendly web application for real-time predictions. Future enhancements aim to integrate real-time weather data and expand accessibility through mobile applications.

Author
dolumohan782
Language
EN