Learning algorithms are procedures that enable a model or system to improve performance from data or experience. They determine how patterns are identified, parameters are updated, and predictions or decisions are refined over time.
also known as data-driven algorithms, are algorithms that determine their own procedure for a given task using data that we provide on previous inputs and desired outputs. Learning algorithms take the data we provide as experience and learn a mapping from input to output, often under constraints that we define. They can then produce new outputs given future inputs. For example, a learning algorithm for making sourdough bread might take several recipes as input, along with information on whether or not each recipe is tasty, and learn which combinations of ingredients make good sourdough.