Training ist der Prozess, bei dem Daten und ein Lernalgorithmus verwendet werden, um die Parameter eines Modells zu bestimmen oder zu verbessern. Während des Trainings passt das System interne Werte wie Gewichte, Split-Punkte oder Biases so an, dass seine Ausgaben besser zur vorgesehenen Aufgabe passen.
The process of determining the ideal parameters (weights and biases) comprising a model. During training, a system reads in examples and gradually adjusts parameters. Training uses each example anywhere from a few times to billions of times. See Supervised Learning in the Introduction to ML course for more information.
Training is the process of presenting a set of data examples to an AI system in order to refine its model. The AI system can improve how it works by analyzing the training data, making predictions, and comparing those predictions against the actual outcome. Then, the AI system uses that information to tune the model to improve accuracy.
The process of identifying a model for a given training data set. For a linear model, this means finding the weights. For a tree, it involves identifying the split points.