Mindful Machines

  The worst performance of the ML( Machine Learning ) Models is due to the Overfitting and Underfittin g  largely. As in the past, we discovered that the generalization is the idea that every model should do but the overfitting and underfitting will go along with them so we generally have to more aware that the model should not do the overfitting and underfitting. A vital factor in determining the objective function from the training data is how well the model generalizes to new data. Generalization is important because the data we receive is only a sample, it is incomplete and noisy. Overfitting:- Overfitting is the bug in the ML which means that the model trains itself very much on the training data set. Overfitting happens when a model learns the detail and noise in the training data to the extent that it negatively influences the appearance of the model on brand-new data. This actually gives us the idea that the noise in the training data set is picked up and learned as id...