Resnet34 is a state-of-the-art image classification model, structured as a 34 layer convolutional neural network and defined in "Deep Residual Learning for Image Recognition". Restnet34 is pre-trained on the ImageNet dataset which contains 100,000+ images across 200 different classes.
However, RestNet is different from traditional neural networks in the sense that it takes residuals from each layer and uses them in the subsequent connected layers (similar to residual neural networks used for text prediction).
Below. on the right-hand side, is Resnet34's architecture where the 34 layers and the residuals from one layer to another are visualized.
Learn how to use Resnet34 Custom Resnet34 Model for Image Classification using fastai and PyTorch: https://blog.roboflow.com/custom-resnet34-classification-model/