Training Residual Neural Network with your own dataset

#python #TensorFlow #Keras

ResNet50 Architecture video link:-

   • RESNET50 Architecture | Residual neur...  

In this video we have trained a ResNet50 model from skratch in python.

You can check out udemy complete course for transfer learning on below link

https://www.udemy.com/course/advanced...



A residual neural network (ResNet) is an artificial neural network (ANN) of a kind that builds on constructs known from pyramidal cells in the cerebral cortex. Residual neural networks do this by utilizing skip connections, or shortcuts to jump over some layers. Typical ResNet models are implemented with double- or triple- layer skips that contain nonlinearities (ReLU) and batch normalization in between.An additional weight matrix may be used to learn the skip weights; these models are known as HighwayNets.[3] Models with several parallel skips are referred to as DenseNets. In the context of residual neural networks, a non-residual network may be described as a plain network.