Crop Whiz is an AI-powered solution designed to assist Indian farmers in making informed decisions about crop selection, fertilizer usage, and pesticide application. It leverages machine learning and deep learning techniques to provide recommendations based on soil and environmental data.
- 🔍 Crop & Fertilizer Recommendation using custom ensemble ML models (achieved 80% accuracy)
- 🌿 Plant Disease Detection using Convolutional Neural Networks (CNNs)
- 🌱 Pesticide Recommendation based on disease prediction
- 🧑🌾 User-Friendly Interface for localized deployment
- 📊 Data-driven Decisions for enhancing productivity and crop health
- Python
- Machine Learning (Random Forest, XGBoost, Voting Classifier)
- Deep Learning (CNN - TensorFlow/Keras)
- Streamlit (for UI)
- Pandas, NumPy, scikit-learn, OpenCV