Software Engineering And Web Development: Explained Recurrent Layers
Exploring popular neural network layers: Recurrent, LSTM, GRU, Transformer, activation functions, loss functions, optimizers & more!
Buy Me a Coffee☕ *Memos: My post explains Recurrent Layer, LSTM, GRU and Transformer. My post explains activation functions in PyTorch. My post explains loss functions in PyTorch. My post explains optimizers in PyTorch. A layer is a collection of nodes to do a specific task. Basically, a Neural Network(NN) consists of 3 layers as shown below: Input Layer: is the 1st layer which accepts data and pass it to a hidden layer. Hidden Layer: is the layer between an input and output layer. can be zero or more hidden layers in a neural network. Output layer: is the last layer which holds a...