A rule-based system use rules to suggest crops based on weather patterns, and other relevant factors. 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.
First we use the data set from kaggle
We preprocess the data using pandas and matplotlib get teh relation between the factors affecting crop and the used Sklearn . We choose logistic regression as our model and predict the crop recommendation and we got overall 95% accuracy on the test data (unknown data)
Finally after building our model we uses Streamlit platorm to deploy our model on streamlit cloud
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