Weight initialization

After the configuration of the network, training starts with initializing the weights' values. A proper weight initialization is important in the sense that all the training does is to adjust the coefficients to best capture the patterns from data in order to successfully output the approximation of the target value. In most cases, weights are initialized randomly. In some finely-tuned settings, weights are initialized using a pre-trained model.