Explore our tools to make informed agricultural decisions.
This project is a crop prediction website that suggests the best crops to plant based on various input features using the K-Nearest Neighbors (KNN) algorithm. The web application is built with Flask.
The Crop Recommendation System employs machine learning to offer personalized crop suggestions based on environmental and soil conditions.
Multiservice app with Crop Yield Prediction built using Django , React and Node.
Saathi - Crop recommendation using ML and plant disease identification using CNN and transfer-learning approach
Agro companion is a soil classification, crop recommendation and crop information website. It helps identify seven types of soils, recommend 20+ crop based on specific factors and also help search information required to grow them.
ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.
A crop recommendation API using a machine learning with an accuracy of 99.18%.
SmartCrop is an AI model designed to assist farmers in determining the most suitable crop to cultivate based on environmental and soil parameters.
3 different machine learning algorithms based crop recommendation system
ML based Smart Crop Recommendation System with Disease Identification, utilizing CNNs. It aids farmers in selecting crops, managing diseases, and boosts productivity by integrating weather and geolocation APIs.
AClimate official website
Crop Recommendation ML Model | Python
Cultivating yield with an intelligent crop recommendation system
Crop Recommendation
Some AIML Projects
A machine learning based website that recommends the best crop to grow, fertilizers to use, and the diseases caught by your crops.
A machine learning model to recommend suitable crops based on soil health conditions.
A neural network-based crop recommendation system leveraging soil and environmental data. Achieved 98% accuracy through hyperparameter tuning and evaluation of two architectures with 2 and 5 hidden layers.
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