Trenér

In the context of computer science, „Trenér“ appears to refer to a term commonly associated with „trainer,“ particularly in the fields of machine learning and artificial intelligence. A trainer is an entity or component responsible for teaching a model by providing it with data in a structured format. During the training process, the trainer adjusts the parameters of the model based on the input data and the corresponding expected outputs, with the aim of minimizing the error in predictions.

The trainer iteratively updates the model using algorithms such as gradient descent and optimizes performance through techniques such as regularization and validation to prevent overfitting. The term may also refer to specific implementations or frameworks that provide training capabilities, allowing developers to build and refine predictive models effectively.

In summary, a „Trenér“ in computer science is fundamentally linked to the process of training machine learning models, emphasizing the role of data, algorithms, and performance optimization in achieving accurate predictions.