This model introduces the best suitable crop for a particular land based upon the rainfall, Soil nutrients levels and weather condition for different districts of Indian sub-continent. So, this application will provide the information about land for farming whether the land is suitable for cultivation of the crop selected or not in different cities and districts. This application also provides information regarding the suitable land for particular types of farming.

• I compared various machine learning approaches for getting the best result and used XGBoost Algorithm for the application.
• Just now the project is in the development phase and I need to make the model much accurate and reliable.

• Add project to your local dekstop using git clone https://github.com/Priyanshu-21/Crop-Prediction.git
• Now, change the directory of your terminal to cd Server
• run command python app.py to run the app.py file in Server folder (app.py is the backend part of the project).
• In your external terminal run npm start to run front end of the project.

• Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
• Please make sure to update tests as appropriate.

MIT