Basic Search vs. Bayesian Optimization | Hyperparameter Optimization

In this video, we review key techniques for hyperparameter optimization, including Grid Search, Random Search, and Bayesian optimization methods like Gaussian processes, SMAC, and TPE. We also explore their advantages, disadvantages, and application in both low and high-dimensional spaces, offering guidelines on when to use each technique effectively. Want to learn more? Check out our course: https://www.trainindata.com/p/hyperparameter-optimization-for-machine-learning