imrhf's starred repositories
SowEasy_Crop-Recommender
"SowEasy " is a Crop Recommendation system that compares various machine learning models and provides the best crop to plant depending on various factors.
Team-2_Crop-Recommendation-System
The Crop Recommendation System aims at suggesting crops based on the user input that consists of the soil quality, rainfall and other apt attributes.
Crop-Recommendation-System-Using-Machine-Learning
Crop Recommendation System Using Machine Learning
Agriculture-Crop-Recommendation-Algorithm
To recommend optimum crops to be cultivated by farmers based on several parameters and help them make an informed decision before cultivation
crop-recommendation-system-based-on-machine-learning-using-python
A machine learning model in python that recommends the best crop to grow based on Soil composition, Ph level, rainfall and geographical location.
Intelligent_CropPrediction_System
An Intelligent Crop Recommendation system using Machine Learning that predicts crop suitability by factoring all relevant data such as temperature, rainfall, location, and soil condition. This system is primarily concerned with performing AgroConsultant's principal role, which is to provide crop recommendations to farmers.
Soil-Analysis-and-fertilizer-prediction-model-for-farmers-using-machine-learning-approach-
The mobile application predicts the suitable fertilizer for the soil using Naive Bayes Classifier based on the history data sets. The history of datasets gets compared with the resultant value to predict the suitable fertilizer. It also helps in directing the farmers to the nearest soil test center. ● Developed using Android. Fuzzy logic technique has been used to predict the fertility of the soil from the questionnaire answered by the end users