Optimizing CNN Performance: A Deep Dive into Image Classification

This article dives into the challenges of training a Convolutional Neural Network (CNN) for image classification, offering valuable insights into optimizing accuracy and addressing dataset imbalances. The exploration of hyperparameters like dropout, epochs, and batch size provides a practical guide for researchers and developers. The discussion highlights the importance of data distribution and its impact on model performance.