JamesZhouSH/Crop-Disease-in-Uganda

# Crop Disease in Uganda In this project we'll be working with a dataset of crop disease images from Uganda. You'll build and train a convolutional neural network to classify images into five categories. In the project you'll learn how to improve the performance of a computer vision model by using pre-trained models and by optimizing training with techniques like Callbacks. By the end of this project, you'll be able to: Explore a crop image dataset. Build and training a convolutional neural network to classify images into five classes. Improve the model by using Transfer Learning and adapting a pre-trained image classification model. Indentify model overfitting. Evaluate model performance using k-fold cross-validation. Utilize Callbacks like Learning Rate Scheduling, Checkpointing, and Early Stopping to optimize training.