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"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.
The AI-Driven Crop Prediction System that applies Machine Learning and AI to analyze weather, soil, and crop data to predict crop health and yield. This system provides farmers with precise predictions, empowering them to make data-driven decisions and enhance their farming practices.
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
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 recommendation Web Application using Machine Learning along with fertilizer and cultivation season recommendation made with flask. The Prediction is performed using Random Forest Model
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.