👉 Residual Math, or Residual Analysis, is a method used in machine learning and deep learning to evaluate the performance of a model by examining the difference between its predictions and actual values, known as residuals. This approach helps in understanding how well the model is capturing the underlying patterns in the data, especially in scenarios where the model's internal representations are not fully optimized. By analyzing these residuals, practitioners can identify biases, outliers, or areas where the model might be failing, guiding further adjustments and improvements to enhance accuracy and robustness.
