Member-only story
I have discussed this before: using sweeps is easy with tools that facilitate logging and monitoring.
Optimize Your Model: Hyperparameter Tuning with Weights & Biases Sweeps. (BTW, you can log anything with Weights & Biases.)
The key point lies in the search methods.
1. Grid Search
Explanation: Grid search is a brute-force search method where every possible combination of hyperparameters from a predefined grid is tested. For example, if you have two hyperparameters with three possible values each, grid search will run nine different training sessions (3 × 3).
2. Random Search
Explanation: Random search selects a random combination of hyperparameters to test from the predefined search space. It samples points at random until a stopping condition is met (e.g., a certain number of iterations or time limit).
3. Bayesian Optimization
Explanation: Bayesian optimization is a more sophisticated method that builds a probabilistic model of the objective function and uses this model to…
