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.
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Updated
Aug 9, 2024 - Jupyter Notebook
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.
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
App for monitoring crop environmental conditions, allowing the farmer to get insight and take better decisions.
Forecasting crop yields is a crucial element of farming, enabling growers to make well-informed choices regarding their agricultural output. This process entails predicting the quantity of crops expected to be harvested within a specific region, taking into account factors like soil composition, climatic patterns, and agricultural techniques.
Crop Prediction using Machine Learning (Classification Use Case)
ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.
This contains only frontend code of the project to run this, you'll have to clone the backend repo in your machine and run the backend with the python scripts first, below is the deployed link where you can check the working of the webApp
METADATA-FARMER ASSISTANCE WEBAPP | AI & ML
"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.
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.
Farmer assistant system VCET Hackathon 2k22
Prediction of suitable crop using soil and weather conditions.
Deployed ML-Backend Server to predict the best crop you should sow in your fields depending on environment conditions.
Build@ARSD - Tech for Good
This Github Repository Contains a machine learning powered crop price prediction application with a firebase connected login and signup
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
Revolutionize your farming with Farmwiser, the ultimate TinyML based Smart Agriculture solution!
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