CIFAR10-VGG16
This post details the implementation of a VGG-16 neural network for CIFAR-10 image classification in TensorFlow. It highlights the use of gradient clipping to improve convergence speed. Key aspects include network layer structure with regularization and normalization techniques, loss computation, and optimization via Adam. The script covers data loading, model creation, training with performance logging, and testing with accuracy measurement.