Agricultural crop recommender system based on climatic conditions

This study presents the development of an agricultural crop recommender system based on climatic conditions usingmachine learning. The system utilizes weather data and other environmental factors to provide recommendations for crops that are most suitable for a given region. To train the ML model, a dataset of previous crop yields and climate data was gatheredand examined. The model was assessed using a number of measures, including precision and accuracy. The results show that the system can accurately predict suitable crops for a given location, making it a valuable tool for farmers and agricultural experts. The system has the potential to improve crop yields and mitigate the impact of climate change on agriculture.