Abstract:  
  
The purpose of this study is to predict crop production using machine learning.  
The paper focuses on predicting the production of crops depending on temperature,  
wind speed, humidity, crop type, and harvestable area.  
  
We have used various machine learning models and compared the results.  
Results were compared against five models, Support Vector Machine (SVM),  
Naive Bayes, Multiple Linear Regression, K-Nearest Neighbor (KNN) and  
Random Forest. Out of which Random Forest yielded the highest accuracy score.