What is Overfitting in Machine Learning and how can it be avoided?
Overfitting is a common problem in machine learning where a model learns to perform exceptionally well on the training data but fails to generalize to new, unseen data. In other words, the model captures noise or random fluctuations in the training data as if they were meaningful patterns,