What are peoples experience with different methods of Hyperparameter Optimization?

Hey everyone,

I'm currently in the process of fine-tuning hyperparameters for a machine learning model. I have been looking into various optimization techniques to push for competitive performance. I'm curious to hear about the community's experiences with different methods of hyperparameter optimization.

Some of the methods I've been considering include:

1. Grid Search: exhaustively searching through a predefined set of hyperparameters. Not ideal?

2. Random Search: random search randomly selects hyperparameter combinations to evaluate. Seems limited for extremely high computational …

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