Machine Learning, Artificial Intelligence, Deep Learning, Neural Networks.
accurately remembers all training data, including noise and unrelated features. Such a model often performs badly on new test or real data that have not been seen before. Because the model treats the training data too seriously, it failed to learn any meaningful pattern out of it, but simply