Overfitting is a common concern for data scientists and machine learning enthusiasts alike. It can be frustrating to have a model that performs exceedingly well in a controlled environment, only for it to fail miserably when faced with new and different data. The culprit behind this phenomenon is a model that is simply too complex. Instead of learning general patterns, the model becomes fixated on memorizing the training data, effectively creating something that is great at regurgitating what it has already seen, but incapable of adapting to new information.
