Project

Overview

Implemented the VGGNet 16 architecture using Pytorch and trained several Convolutional Neural Networks on the CIFAR10 dataset. Learned about different optimizers such as Adam, AdamW, and SGD and learned about learning rate schedulers to optimize results. Achieved more than 92 percent test accuracy on the CIFAR10 dataset.