stephenkinuthia-cell/Crop-Disease-Classification

This project builds and optimizes a convolutional neural network to classify crop disease images from Uganda into five categories using transfer learning and training optimization techniques. # 🌿 Crop Disease Classification in Uganda ## 📘 Project Overview This project focuses on classifying crop diseases using images from Uganda. It applies advanced techniques in computer vision and deep learning to create a robust image classification model. The project is part of the AI curriculum from **WorldQuant University**, and it demonstrates how to build, optimize, and deploy convolutional neural networks (CNNs) using PyTorch. By the end of this project, you will be able to: - Explore and preprocess image datasets. - Build CNNs to classify crop diseases. - Use transfer learning for improved performance. - Apply callbacks to optimize training. - Evaluate models using cross-validation. - Understand the socio-environmental impact of data use in AI. --- ## 🚀 Project Name **Crop Disease Classification in Uganda** ## 📌 Description This project builds and optimizes a convolutional neural network to classify crop disease images from Uganda into five categories using transfer learning and training optimization techniques. ## 🎯 Motivation / Problem Solved In Uganda and many other developing regions, crop diseases significantly impact agricultural productivity and food security. Automating crop disease detection can help farmers take early action, reduce losses, and increase yields. This project addresses the problem using AI and machine learning. ## ✨ Features - Visualize and explore a real-world dataset - Build custom CNNs for multiclass classification - Apply transfer learning using pre-trained models (ResNet) - Implement advanced training callbacks - Evaluate performance using k-fold cross-validation - Raise awareness about AI’s environmental and ethical impact ## 🛠️ Tech Stack - **Programming Language**: Python - **Deep Learning Framework**: PyTorch - **Tools & Libraries**: torchvision, numpy, matplotlib, sklearn ## 📚 Lessons ### 🔧 Lesson 1: Fix My Code **Summary**: Investigated common errors in PyTorch's `nn.Sequential` models. **Topics Covered**: - Incorr …