What is automated hyperparameter tuning in Python machine learning?
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What is automated hyperparameter tuning in Python machine learning?
Automated hyperparameter tuning is a process that optimizes the parameters of machine learning models automatically, improving performance.
How does it differ from manual tuning?
Manual tuning requires human intervention to adjust parameters, while automated tuning uses algorithms to find the best settings.
What are some popular libraries for this in Python?
Some popular libraries include Optuna, Hyperopt, and Scikit-learn's GridSearchCV and RandomizedSearchCV.
Can you give an example of using Optuna for tuning?
Sure! You can define an objective function that trains your model and uses Optuna to optimize hyperparameters like learning rate and depth.
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