🚀 Sharing my end-to-end ML project: Krishi Rakshak — a crop disease classifier built with efficientnet_b0 for smallholder farmers.
⚙️ Model Highlights:
90%+ accuracy on PlantVillage (38 classes)
Trained with AdamW, scheduler, early stopping
Used weighted loss to handle class imbalance
📊 Evaluation:
Manual metric validation + confusion matrix
Precision, recall, F1, per-class accuracy
🧩 Deployment:
PyTorch + Gradio UI, multilingual support
Designed for light, modular inference
🔗 GitHub: https://github.com/VIKAS9793/KrishiRakshak.git
📹 Demo: https://drive.google.com/file/d/1PDxYq5rOuCXZAldZlSd6Q3M5WIGXEtbJ/view?usp=drivesdk
Built independently from scratch — feedback welcome from ML/AgriTech community on optimization or scaling for noisy field data.
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