Bear in mind from the last write-up, this is similar to saying that changing the weights and biases decreases the reduction operate to its minimum. Most ML issues operate like that. As an example, linear regression. Gaussian processes are well-liked surrogate versions in Bayesian optimization used to do hyperparameter optimization. https://mynichedirectory.com/listings13105911/natural-language-processing-for-dummies