Dynamic: Difference between revisions

In machine learning, the term "dynamic" can refer to various concepts depending on its context. Generally speaking, this indicates a system's capacity for change or adaptation in response to new information or input. Examples include updating models based on new training data or adapting robot behavior according to environmental changes. This article will examine these different interpretations of "dynamic" in machine learning and how they are utilized in practice.