Bayesian Optimization, Machine Learning, AI, Hyperparameter Tuning.
model is then used to make educated guesses about where in the parameter space the objective function might attain its optimal value. The process involves two main components: the surrogate model and the acquisition function. The surrogate model, often a Gaussian process, estimates the objective