👉 Smoothification is a technique in machine learning, particularly deep learning, used to reduce computational complexity by simplifying or reducing the size of model parameters. This process involves adjusting the values of weights and biases within a neural network to achieve better performance on a given dataset. The goal is to minimize the number of parameters required for a model, which can be achieved through various techniques such as pruning, dropout, and regularization. Smoothification is often used in conjunction with other machine learning techniques, such as feature selection
