Weighting networks refers to the process of assigning different levels of importance, or "weights," to various connections within a network. This concept is commonly used in fields like machine learning and neural networks, where the strength of connections between nodes can significantly influence the output of the model. By adjusting these weights, the network can learn from data and improve its performance over time. In a weighted network, connections can represent various relationships, such as the strength of a friendship in a social network or the bandwidth of a link in a computer network. The weights help to quantify these relationships, allowing for more nuanced analysis and decision-making based on the network's structure and dynamics.