Overfitting is a common problem in machine learning where a model performs well on training data but poorly on new data. This question aims to explain the concept in simple terms and explore techniques to prevent it.

Contributors can discuss methods like cross-validation, regularization, and data augmentation. Understanding overfitting is crucial for building reliable models. This discussion will help beginners improve their model performance and generalization.