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Model Evaluation
ML Model metrics, overfitting/underfitting, and other methods to assess ML model performance
Overfitting vs Underfitting
History In machine learning, the loss (or cost) function is a measure of how well the model's predictions match the true values of the input data. The loss function is used to guide the optimization process of the model, with the goal of minimizing the loss. The history of the loss function is used to evaluate the performance of the model during the training process. The loss history is a record of the values of the loss function at each iteration (or epoch) of the training process. It is ty
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