Crop Recommendation system

GOAL

A rule-based system use rules to suggest crops based on weather patterns, and other relevant factors

DESCRIPTION

I will use Machine learning algorithm like logistic regression and randomforest to predict which crop would by relevent to grow in that condition and environment
In this logistic regression model is used to predict crop recommendation system while random forest is used to check quality of soil

MODELS USED

In this project I have used Logistic regression and random forest model. Because it is very efficient for classification problems

LIBRARIES NEEDED

streamlit
seaborn
pandas
matplotlib.pyplot
numpy
ML algorithms
sklearn

VISUALIZATION

ACCURACIES

Accuracies and results of Algorithms used
The accuracy score achieved using Logistic Regression in crop recommendation is: 95.45 %
The accuracy score achieved using Random Forest in soil fertility prediction is: 100 %

CONCLUSION

This type of system is relatively simple to implement and may be suitable for smaller farms with less complex data needs. A crop recommendation system can be a valuable tool for farmers, helping to increase crop yield, optimize resource use, and reduce the risk of crop failure due to environmental factors.

Deployment

To deploy this project run the given snippet in terminal.

  streamlit run main.py