This application assists farmers in selecting the optimal crop to cultivate considering soil composition and environmental conditions. By providing information such as nitrogen phosphorus and potassium levels as well as temperature humidity pH and rainfall users receive tailored recommendations for the most suitable crop out of a selection of 22 options. This is a supervised multi-class classification problem.
Technologies used in the project:
- Python
- Jupyter
- Streamlit
- Numpy
- Pandas
- Sklearn