About this document
Machine Learning for Crop Yield Prediction by Hemant Chaudhari is a document available to read on EtoBox.
This study focuses on developing a machine learning model to predict crop yield based on historical agricultural data, considering factors like soil quality and weather conditions. The methodology involves data cleaning, feature engineering, and training a Random Forest Regressor, achieving strong predictive capabilities with an R² value of 0.87. Future enhancements may include integrating remote sensing data and exploring deep learning approaches for improved accuracy.
- Author
- Hemant Chaudhari
- Language
- EN