Hyperparameter tuning is the process of selecting the best configuration settings for a machine learning algorithm to improve its performance. Unlike model parameters, hyperparameters are set before training and cont...

Precision and accuracy are two commonly used evaluation metrics in machine learning, but they measure different aspects of model performance. Although they are often confused, understanding the difference between the...