There are 3 repositories under crop-prediction topic.
An all purpose flutter app for farmers made under Food and Agriculture theme in Accelathon hackathon
ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.
Developed a machine learning-based crop prediction model to assist farmers in making informed decisions about crop selection, planting, and harvesting.Integrated weather and geolocation APIs along with a web page for simplified user experience.
The model focuses on predicting the crop yield in advance by analyzing factors like district (assuming same weather and soil parameters in a particular district), state, season, crop type using various supervised machine learning techniques. This helps the farmers to know the crop yield in advance to plan and choose a crop that would give a better yield.
The Crop Management System is a machine learning-based project designed to provide predictions and recommendations for farmers.
A mobile application involving machine learning to recommend crop variety and also predict crop yield.
SmartCrop: Intelligent Crop Recommendation
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.
Farmer assistant system VCET Hackathon 2k22
Build@ARSD - Tech for Good
This Github Repository Contains a machine learning powered crop price prediction application with a firebase connected login and signup
"Excited to share my latest project on LinkedIn: a crop yield prediction ML model deployed with Streamlit! 🌱 Leveraging the power of Stochastic Gradient Descent regression(SGD) algorithm, this tech-driven solution boasts an impressive 94% accuracy on both training and testing data.
This web application uses Machine Learning to recommend crop, fertilizer, pesticide and storage process based on various variables. Algorithm used is SVM for multi-classification
With this project, we hope to help solve the problems faced during farming and help the farmers, government and consumer by highlighting the advantages of using Machine Learning to predict crop yield and present an alternate supply chain by using block chain and decentralized the entire process.
METADATA-FARMER ASSISTANCE WEBAPP | AI & ML
Deployed ML-Backend Server to predict the best crop you should sow in your fields depending on environment conditions.
ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.
Revolutionize your farming with Farmwiser, the ultimate TinyML based Smart Agriculture solution!
Prediction of suitable crop using soil and weather conditions.
Crop Prediction using Machine Learning (Classification Use Case)
Developed a machine learning-based crop prediction model to assist farmers in making informed decisions about crop selection, planting, and harvesting.Integrated weather and geolocation APIs along with a web page for simplified user experience.
ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.
App for monitoring crop environmental conditions, allowing the farmer to get insight and take better decisions.
Crop recommendation Web Application using Machine Learning along with fertilizer and cultivation season recommendation made with flask. The Prediction is performed using Random Forest Model